EARTHWORM ECOLOGY, HEAVY METALS AND TOTAL PETROLEUM HYDROCARBON 
ASSESSMENT OF AN OIL SPILL SITE IN AGAYE, LAGOS STATE, NIGERIA. 
 
 
By 
 
 
 
AEMERE OGUNLAJA 
 
MATRIC No. 112614 
 
 
B.Sc (Hons) MICROBIOLOGY (AAU), M.Sc ENVIRONMENTAL 
BIOLOGY/ECOLOGY (U.I) 
 
 
 
 
A THESIS IN THE DEPARTMENT OF ZOOLOGY 
 
 
SUBMITTED TO THE FACULTY OF SCIENCE IN PARTIAL FULFILLMENT OF 
THE REQUIREMENT FOR THE AWARD 
 
OF 
 
DOCTOR OF PHILOSOPHY 
 
Of the  
 
UNIVERSITY OF IBADAN, IBADAN 
 
 
 
 
 
 
 
AUGUST, 2014 
 
 
ABSTRACT 
 
Agaye has experienced frequent spills of premium motor spirit due to pipeline vandalization. 
Over time,the spills have contaminated the water sources and farmlands, and with the attendant 
inferno, destroyed the soil biota. There is dearth of scientific information on effect of the spills in 
this area. This study investigated the abundance and heavy metals level of earthworm, and 
determined the physico-chemical parameters of the groundwater, surface-water and soil in 
Agaye. Twenty topsoil samples (0.5m x 0.5m x 0.2m) were randomly collected monthly within 
the epicenter of the spill and 500 meters away from the spill between June 2007 and April 2009 
for earthworm analysis. The earthworms were handpicked, identified with standard keys and 
counted. Cadmium, Copper, Nickel, Zinc, Manganese and Lead concentrations in tissue of the 
two most abundant earthworm species were determined using atomic absorption 
spectrophotometry.  Seven existing water sources (GW1 to GW5 for groundwater; SW1 and SW2 
for surface-water) were sampled along the transect of spill. Soil samples (S1-S5) were collected 
around same loci of the groundwater sites. GW6 and S6 served as control, being 500m away from 
spill. Samples collected every two months were analysed for pH, Total Petroleum Hydrocarbon 
(TPH) and the heavy metals according to APHA, 1995. Earthworm diversity and abundance 
were analysed using Shannon Weiner (HS) and Mann-Whitney respectively while data on 
physicochemical parameters were analysed with ANOVA at p=0.05. In the first 12 months, 
Lybiodrilus violaceous was the only earthworm encountered within the epicenter while L. 
violaceous and Dichogaster modigliani (H = 0.3) were found 500m away. In the last 11 months, 
L. violaceous, D. modigliani, Ephyriodrilus afroccidentalis and Heliodrilus lagosensis were 
encountered in both sites (H = 0.3, at the epicenter; H = 0.9, 500 m away). The abundance of 
2
earthworm 500m away (204 earthworms/m ) was significantly higher than within the epicenter 
2
(45 earthworms/m ) in the first 12 months but not significantly different in the last 11 months. 
The concentration (μg/g) of Lead, Cadmium, Copper, Zinc and Manganese in L. violaceous was 
0.4±0.02, 0.2±0.003, 0.1±0.003, 5.5±0.02 and 3.7±0.002 respectively; Nickel was not detected. 
Only zinc (6.7±0.4) and Cadmium (0.06±0.002) were detected in D. modigliani. Cadmium (0.0–
0.1 mg/L) and Nickel (0.1-1.6 mg/L) levels in GW1 to GW5 were higher than control (GW6) and 
NESREA drinking water limits. Cadmium, Copper and Nickel levels (mg/L) in SW1 and SW2, 
(ranged 0.0-0.1, 0.07-0.7 and 1.5-2.8 respectively) were higher than NESREA permissible limit. 
Mean concentrations of TPH were significantly higher in surface-water (3.3±0.5 mg/L) than 
groundwater (1.3±0.6 mg/L) while pH was significantly lower in groundwater than surface-
i 
 
 
water. Mean pH at S1-S5 ranged from 5.3±0.04 to 6.5±0.02. Soil TPH, cadmium and copper 
reduced significantly during the last 11 months. Soil TPH level was significantly higher than 
control soil. The increase in number and species of earthworm in the last 11 months indicated 
possible remediation of the environment. The high concentrations of heavy metals in the 
earthworms suggest possible roles in bioaccumulation. The higher levels of heavy metals and 
total petroleum hydrocarbon in surface and groundwater indicated that they are unsafe for 
drinking.  
 
Keywords: Oil spillage, Heavy metals, Total petroleum hydrocarbon, Earthworm abundance. 
 
Word Count: 498 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ii 
 
 
 
 
CERTIFICATION 
 
I certify that this work was carried out by OGUNLAJA, Aemere of the Department of Zoology, 
University of Ibadan Under my supervision. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
-------------------------------------------------- 
 
Supervisor 
Dr. Olajumoke Morenikeji 
B.Sc , M.Sc, Ph. D (Ibadan) 
Department of Zoology, 
University of Ibadan,Ibadan, 
Nigeria. 
 
 
 
 
 
 
 
 
 
 
 
 
 
iii 
 
 
 
 
DEDICATION 
 
This research work is dedicated to my husband and children, Mr O.O. Ogunlaja, Simi, Rotimi 
and Wemimo. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
iv 
 
 
 
 
ACKNOWLEDGEMENT 
 
I am grateful to my supervisor, Dr. (Mrs.) Olajumoke A. Morenikeji for her counsel, 
encouragement and support during this research. I am also thankful to Prof. S.O. Owa for his  
support through the course of this work and his relentless effort to see that the work comes to a 
fruitful completion. I sincerely thank members of Staff of the Zoology Department, University of 
Ibadan for their advice and support. I specially thank Prof. Hassan for his fatherly role during the 
course of this work.  
I appreciate my children, Simi, Rotimi, Wemimo and Tina for their understanding and support 
throughout the period of this study. during which I might not have been there for them fully. I am 
very much indebted to my treasured husband, Mr. O.O. Ogunlaja  who was always ready to stand 
in for me in the family whenever the need arose.  
My appreciation goes to the entire staff of Biology and Chemistry Department, Redeemer‟s 
University, Mowe, Ogun State, especially Mr Popoola, Mr. Sojinu, Mr. Akanbi and Mr. 
Adebayo for their technical support. My appreciation also goes to my colleagues and friends for 
their selfless, useful and helpful contribution towards the successful completion of this research 
work. I also thank my friends, so many to mention that stood by me emotionally and otherwise 
when I needed them. 
To my family- The Aigbologas, especially my Father and Mother, I am very thankful to you. I 
am grateful also to my in-laws, the Ogunlajas and everyone who in one way or the other 
contributed to my well being- it is impossible to mention all.  
Finally I want to thank God for this wonderful opportunity.  
 
 
 
 
 
 
 
 
 
 
 
 
v 
 
 
 
 
TABLE OF CONTENTS 
                                                                                                
 Contents                                                                                                                          Page                              
 
Abstract…………………………………………………………………………………….i 
Certification………………………………………………………………………………..ii 
Dedication………………………………………………………………………………….iv 
Acknowledgement………………………………………………………………………….v 
Table of Contents…………………………………………………………………………..vi 
List of Tables……………………………………………………………………………….x 
List of Figures…………………………………………………………………………….xiii 
List of Plates………………………………………………………………………………xv 
CHAPTER ONE………………………………………………………………………… .1 
1.0 INTRODUCTION …………………………………………………………………….1 
1.1 Environmental pollution……………………………………………………………1 
1.2 Petroleum sector in Nigeria……………………………………………………......2 
1.3 Remediation of petroleum contaminated sites……………………………………..4 
1.4 Earthworms……………………………………………………………………......5 
1.5 Research rationale………………………………………………………………….6 
1.6 Aim and Objectives………………………………………………………………...7 
CHAPTER TWO………………………………………………………………………….8 
 
2.0 LITERATURE REVIEW……………………………………………………………..8 
2.1  Pollution…………………………………………………………………………….......8 
2.2  Petroleum……………………………………………………………………………….10 
       2.2.1 Constituents of petroleum………………………………………………………11 
       2.2.2 Petroleum production………………………………………………………......12 
       2.2.3 Major petroleum products…………………………………………………......13 
2.3 Petroleum pollution and its ecological effects………………………………………...15 
2.4 Health effects of petroleum pollution…………………………………………….......18 
vi 
 
 
     2.4.1 Benzene………………………………………………………………………....19 
     2.4.2 Toluene…………………………………………………………………………….19 
     2.4.3 Ethylbenzene………………………………………………………………………20 
     2.4.4 Xylene……………………………………………………………………………...20               
     2.4.5 Metals………………………………………………………………………...........21  
2.5 Oil Production in Nigeria.................................................................................................26       
     2.5.1 Nigeria oil refineries.................................................................................................27  
    2.5.2 Nigeria Oil spills and their ecological impact...........................................................29  
2.6 Remediation techniques for oil spills...............................................................................33 
2.7 Bioremediation techniques...............................................................................................35 
2.8Earthworms and their ecological importance....................................................................37 
       2.8.1 Earthworm use for remediation and ecotoxicity....................................................38 
       2.8.2 Earthworms and heavy metals...............................................................................41     
      2.8.3 Action of earthworms in remediation.....................................................................42 
2.9 Physicochemical parameters............................................................................................43 
CHAPTER THREE.............................................................................................................44 
3.0 MATERIALS AND METHODS..................................................................................44 
3.1 Study area........................................................................................................................44 
3.2 Sample collection and analysis - Quality assurance and quality control.........................51 
      3.2.1 Water and Soil sampling.........................................................................................51  
3.3 Physicochemical analyses................................................................................................53 
      3.3.1 Water analyses........................................................................................................53 
 3.3.1.1  Heavy metals................................................................................................53 
 3.3.1.2  pH.....................................................................................................……… 53 
           3.3.1.3  Temperature...................................................................................................54 
           3.3.1.4 Total Dissolved Solid (TDS)...........................................................................54 
vii 
 
 
3.3.1.5   Total Hardness (TH)....................................................................................................54 
3.3.1.6   Conductivity.....................................................................................................................55 
3.3.1.7  Chloride (Cl-) and Alkalinity.......................................................................................55 
3.3.1.8  Sulphates............................................................................................................................55  
3.3.1.9   Phosphate..........................................................................................................................55  
3.3.1.10 Nitrate.................................................................................................................................56  
3.3.1.11  Total petroleum hydrocarbon..................................................................…………56 
3.3.2  Soil analysis..........................................................................................................................58 
3.3.2.1    Heavy Metal Analysis..............................................................................................58 
 3.3.2.2    pH...........................................................................................................................58 
3.3.2.3    Conductivity....................................................................................................................59 
3.3.2.4     Sulphates.........................................................................................................................59 
3.3.2.5    Phosphate........................................................................................................................59 
3.3.2.6    Nitrate...................................................................................................................60 
3.3.2.7    Potassium................................................................................................................... …60 
3.3.2.8    Sodium........................... …......................................................................................... …61 
3.3.2.9    Calcium............................................................................................................................ 61 
3.3.2.10   Total Organic Carbon and Total Organic Matter  
                  (TOC and TOM)..........................................................................................................61 
3.3.2.11   Total Extractable petroleum Hydrocarbon (TPH).....................................62 
3.4 Field study on earthworm distribution and abundance.................................................62 
viii 
 
 
3.5 Determination of levels of contaminants in earthworm species…..……..63 
3.6 Sensitivity test………………………………………………………………………………….63  
      3.6.1 Test animal and soil preparation………………………………………..………63 
      3.6.2  Fourty – eight hours (48h) Avoidance Test………………………………..64 
      3.6.3 Seven days Survival Test………………………………………………………….. 64  
3.7 Experimental set-up for bioremediation study……………………………………65 
      3.7.1 Earthworm application……………………………………………………….……...65 
3.8 Statistical Analyses……………………………………………………………….………......69  
 
CHAPTER FOUR...........................................................................................................70 
4.0 RESULTS...................................................................................................................70 
4.1 Heavy metal concentrations in water samples.............................................................70  
4.2 Concentration of sulphate, nitrate, phosphate and TPH in water samples over  
      study period............................................................. ....................................................75 
4.3 Heavy metal concentration in soil samples..................................................................80  
4.4 Other physicochemical parameters in soil samples......................................................85 
4.5 Soil / Weather conditions of the study area..................................................................85 
4.6 Earthworm abundance and distribution........................................................................89 
4.7 Correlation of physicochemical parameters with earthworm abundance...................109 
4.8 Earthworm toxicity tests.............................................................................................114 
4.9 Ex-situ bioremediation study......................................................................................114 
CHAPTER FIVE……………………………………………………………………….125 
5.0 DISCUSSION………………………………………………………………………125 
5.1 Water quality ………………………………………………………………………..125 
5.2 Earthworm abundance, distribution and densities…………………………………..127 
5.3 Effect of physiochemical/climatic parameters on earthworm abundance…………..128 
5.4 Correlation between some physiochemical parameters and earthworm abundance…129 
5.5 Bioremediation……………………………………………………………………....130 
CHAPTER SIX…………………………………………………………………………131 
6.0 CONCLUSION……………………………………………………………………..131 
ix 
 
 
LIST OF TABLES 
Table 2.1  Petroleum Distillation Products.....................................................................14 
Table 2.2          Oil spill data: SPDC 1995-2013....................................................................31 
Table 2.3  Incidents of Oil pipeline explosion Disaster in Nigeria (1998-2008)…………32  
Table 3.1 Sampling points, designation, description and GPS locations ………………...52  
Table 3.3        Experimental set-up for bioremediation study………………………………….66 
Table 3.4        A modified Small-Scale Bioremediation Sampling Plan…………………….…68 
Table 4.1 Mean concentrations of heavy metals in water samples compared  
    with WHO/NESREA standards…………………………………………….…….73 
Table 4.2      Mean concentrations of heavy metals in water samples from each  
                       sampling points………………………………………………………………74 
Table 4.3 Monthly mean concentrations of sulphate, nitrate, phosphate, pH, temperature, 
TDS, TH, alkalinity, conductivity and chlorine in well water samples………76 
Table 4.4     Mean concentrations of sulphate, nitrate, phosphate in water samples  
                     compared with WHO/NESREA standard…………………..…………………78 
Table 4.5     Mean concentrations of other physicochemical parameters in water samples                         
compared with WHO/NESREA standards……………………………………79 
Table 4.6     Mean concentrations of heavy metals in soil samples from each  
sampling point…………………………………………………………………83 
Table 4.7      Mean concentrations of heavy metals and TPH in soil samples compared with 
control (June 2007 – April, 2009)……………………………………………..84 
Table 4.8    Monthly mean concentrations of TOC, TOM, TPH, sulphate, nitrate and  
x 
 
 
                    phosphate in soil samples (June 2007 – April, 2009)………………….......86 
Table 4.9   Monthly Average temperature, moisture and pH of soil 
                  (June 2007 – April, 2009)…………………………………………………...s87 
Table 4.10  Monthly average rainfalls, temperatures and relative humidity  
                   in Lagos area………………………………………………………………...88 
Table 4.11  Monthly number of earthworm species found in the epicentre of spill……...91  
Table 4.12   Weight of earthworm species found in the epicentre of spill……………….92  
Table 4.13    Number of earthworm species found 500m away from the spill…………..93 
Table 4.14   Weight of earthworm species found 500m away from the spill…………….94 
Table 4.15   Heavy metal accumulation in L.violaceous and D.modiglani species………108 
Table 4.16 Correlation of earthworm species with heavy metal concentrations and                        
other parameters within the epicenter of oil spill…………………..............110 
Table 4.17  Correlation of earthworm species and other parameters 500m away                            
from oil spill………………………………………………………………..111 
Table 4.18  Percentage means of surviving earthworm species…………………………115   
Table 4.19  Percentage means of migrated earthworm species………………………….116 
Table 4.20 Mean concentrations of Total Hydrocarbon in soil samples for                              
bioremediation study………….……………………………………….....117 
Table 4.21 Mean concentrations of Copper in soil samples for bioremediation study…118 
Table 4.22  Mean concentrations of Lead in soil samples for bioremediation stud….....119 
xi 
 
 
Table 4.23  Mean concentrations of Vanadium in soil for bioremediation study……………120 
Table 4.24   Mean concentration of zinc in soil samples for bioremediation study…………121 
Table 4.25  Mean concentrations of manganese in soil samples for bioremediation study….122 
Table 4.26  Mean concentrations of Cadmium in soil samples for bioremediation study…..123 
Table 4.27   Mean concentrations of Chromium in soil samples for bioremediation study…124 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
xii 
 
 
LIST OF FIGURES 
 
            Page  
 
Fig.3.1  Map of Lagos state indicating Ije-Ododo and highlighting sampling points…………46 
Fig.3.2   Picture of experimental set-up for bioremediation study……………………………67 
Fig 4.1  Temporal variation of the heavy metal profile for ground water  
              (GW1 and GW5)……………………………………………………………………..71 
Fig. 4.2  Temporal variation of the heavy metal profile for surface water  
              (SW1 and SW2)……………………………………………………………………...72 
Fig.4.3  Monthly variation of sulphate, nitrtate and phosphate……………………………….73 
Fig. 4.4 Mean concentrations of heavy metals in soil samples between June, 2007             
              
             and Apr, 2009………………………………………………………………………...81 
 
Fig.4.5  Mean concentrations of heavy metal in soils from wetland between June 2007  
              and April 2009……………………………………………………………………….82 
Fig. 4.6  Total earthworm species in epicenter and 500m away from spill…………………...90 
Fig. 4.7  Comparison of soil chromium concentrations and population densities of 
               L. violaceous and D. Modigliani (epicenter and 500m away from spill)…………...96 
Fig. 4.8  Comparison of soil cadmium concentrations and population densities of  
               L. violaceous and D. Modigliani (epicenter and 500m away from spill)…………....97 
Fig. 4.9   Comparison of soil zinc concentrations and population densities of  
               L. violaceous and D. modigliani (epicenter and 500m away from spill)……………98 
Fig. 4.10 Comparisons of soil lead concentrations and population densities of  
               L. violaceous and D. Modigliani (epicenter and 500m away from spill)……………99 
Fig. 4.11 Comparison of soil manganese concentrations and population densities of  
              L. violaceous and D. modigliani (epicenter and 500m away from spill)…………….100 
 
Fig.4.12 Comparison of soil copper concentrations and population densities of 
              L. violaceous and D. modigliani (epicenter and 500m away from spill)………….101 
xiii 
 
 
Fig. 4.13 Comparison of soil nickel concentrations and population densities of  
              L. violaceous and D. modigliani (epicenter and 500m away from spill)………….102 
Fig. 4.14 Comparison of soil vanadium concentrations and population densities of  
              L. violaceous and D. modigliani (epicenter and 500m away from spill)………….103 
Fig. 4.15 Comparison of L. violaceous abundance in the epicenter of oil spill and 500m         
away from spill…………………………………………………………………….104 
Fig. 4.16 Comparison of D. modigliani abundance in the epicenter of oil spill and                                      
               500m away from spill…………………………………………………………….105 
Fig. 4.17 Comparison of E.afroccidentalis  abundance in the epicenter of oil spill and                 
500m away from spill………………………………………………………………106 
Fig. 4.18 Comparison of H. lagosensis  abundance in the epicenter of oil spill and                 
500m away from spill………………………………………………………………107 
Fig. 4.19 Correlation of climatic parameters with earthworm species abundance within the 
epicenter of oil spill………………………………………………………………..112 
Fig. 4.20 Correlation of climatic parameters with earthworm species abundance 500m away     
from oil spill………………………………………………………………………..113 
 
 
 
 
 
 
 
 
 
 
xiv 
 
 
LIST OF PLATES 
 
Plate 3.1     Resultant inferno in Agaye settlement, Iba LSDC, Ojo LGA,  
                  Lagos state after Oil Spill……………………………………….……….47 
Plate 3.2    Water body in Agaye after oil spill and inferno…………………………48 
Plate 3.3    Agaye vegetation after oil spill and inferno……………………………..49                                                                      
Plate 3.4   A farmland after oil spill and inferno…………………………………….50
xv 
 
 
                                                      CHAPTER ONE 
   1.0                                             INTRODUCTION 
 
              1.1   Environmental Pollution 
 
Pollution continues to be an issue of concern to mankind. It can be traced to the 
emergence of the human race and his ignorant use of toxic materials like cadmium 
used in building materials and glazing pigment more than 5000 years ago and the use 
of mercury to alleviate teething pains and as treatment for syphilis by the Romans 
between 1300 and late 1800 (Lars, 2003). The awareness of pollution escalated 
overtime with increasing human population, increase in industrialization and 
consequently adverse health effect linked with pollution became evident. However, 
exposure to pollutants remarkably increased with a steep increase in heavy metal 
th
production by the 19  century onward for more than 100 years, (Nriagu, 1996). 
 Naturally, the conditions of the environment, both biotic and abiotic, mediate to 
support man and other living organisms but one major stress on the environment 
remains the uncompromising result of pollution, (Rapport et al., 1985). The presence 
of substances, be it chemicals, gases or metals is not the problem by itself but the 
presence of such things in wrong places, amounts and time. This results in changes 
in the environment that could be acute or chronic, affecting organisms, at their 
cellular, molecular, organ level or even future generation by mutation (Lundberg and 
Moberg, 2003; Somers et al., 2004). Such substances which when introduced into 
the environment cause pollution are pollutants.  
 The word pollution comes from a Latin word “pollure” which means to “defile” 
or render “unclean” (Osibanjo, 1986). Pollution can be defined as the presence, in 
the environment of significant amount of unnatural substances or abnormally high 
concentration of natural constituents at a level that causes undesirable effects, 
(Johnson et al., 1997). Pollutants are actually “resources out of place”, being too 
much in a system and thus constituting an insult or stress to that` system, 
(Kormondy, 1976). Pollutants could act as stimulants, terminating or initiating 
biological processes. The interference of pollutants in the environment results in 
environmental degradation. Environmental degradation is the process through which 
1 
 
 
an ecosystem‟s capacity to support a constant quality of life is reduced (Johnson et 
al., 1997). Pollutants alter the dynamics and development of an ecosystem (Sattirn, 
1981). Pollutants are from various sources including agricultural, industrial and 
arthropogenic.  Pollution from fossil fuels is one of the major environmental 
st
challenges in the 21  century (Orebiyi and Awomeso, 2008) this is as a result of 
increasing energy demand; the most common fossil fuel in use is petroleum. 
 1.2 Petroleum sector in Nigeria 
The word petroleum is derived from the two Latin words petra which means 
rock and oleum which means oil (Groysman, 2014). Crude oil is also referred to as 
black gold, (Watts, 2004). It appears black, dark brown, yellowish, or even greenish 
liquid and it is found in formations in the earth. It is a substance, generally liquid, 
occurring naturally in the earth and composed mainly of mixtures of chemical 
compounds of carbon and hydrogen with or without other nonmetallic elements such 
as sulphur, oxygen and nitrogen usually formed by a complex and incompletely 
understood series of chemical reactions from organic material laid down in previous 
geological eras (Wallington, et al., 2006). Based on their various sources, crude oils 
vary widely in both physical and chemical properties (Steffens et al., 2009).  
The petroleum sector plays vital roles in the energy and economy of virtually 
every country in the world. In Nigeria, the petroleum industry is the mainstay of the 
economy contributing largely to the nation‟s GDP, and 90% of foreign exchange 
(Ogunleye, 2008). The activities of the petroleum sector ranging from exploration, 
exploitation, refining to distribution of their products, leave behind trails of pollution 
of various degrees in the environment. Over the last few years, particularly in the last 
decade; resource exploitation, environmental pollution, mode and means of 
appropriation of the revenue derived from oil, mode of information dissemination as 
regards risk associated with the oil industries‟ activities, have generated intense 
social conflict in the Niger – Delta (NDES, 1997). It has resulted to frequent 
vandalization of oil installations, overall breakdown of economic activities and 
kidnapping of expatriates and indigenes associated with the oil industry. Niger Delta 
remains the most impacted region by oil spillages (Ordinioha and Brisibe, 2013). 
However, the issues of vandalization of oil installations have been rampant in recent 
2 
 
 
times and have not been restricted to the Niger – Delta region alone. A number of 
fire blasts have been reported in various parts of the country resulting either from 
activities of vandals, construction workers or as a result of leakage from obsolete 
pipes used for distributing petroleum products around the nation. In the last 10 years, 
16,083 pipeline breaks had been recorded; 398 (2.4%) were due to ruptures and 15, 
685 (97.5%) of the breaks were due to the activities of vandals (Ogbeni, 2012). A 
report by a newspaper outfit USTODAY (2006), focused on fires resulting from 
explosions at oil pipelines in Nigeria from the year 1998 to 2003; this they reported 
often caused large numbers of casualties. A total of 12 incidents were recorded, and 
more than 1,000 people were reported killed by such occurrences (an average of 
about 83 deaths per incident). Several tons of petroleum products, especially gasoline 
are usually spilled in such vandalized sites and this result into changes in the 
environment which has deleterious effects on organisms. More importantly, the 
environment remains polluted due to contamination of the soil and water, the 
alteration of diversity and population of soil fauna and flora. The polluted 
environment continues to cause health hazards long after the incident is forgotten.  
The environmental problems in Nigeria surrounding the extraction of oil and 
the distribution of oil products are extensive. Pollution from oil production and 
distribution causes soil erosion, groundwater and marine area contamination, air 
pollution and severe health problems for the indigenous communities surrounding oil 
production and other such communities with incidences of vandalization (UNEP, 
2006). 
A major geographical area exposed to oil spills in Nigeria is the Niger-Delta 
2
area. The Niger Delta located in the central part of southern Nigeria is a 40,000 km -
2
70,000km  sedimentary basin widely considered to be of global economical 
significance because of the vast mineral deposits, especially crude oil and gas. The 
Niger - Delta in Nigeria is a notable region for oil and gas exploration and 
production in the world, it is the largest delta in Africa and third largest in the world 
(HRW, 1999). It is the most affected area in terms of oil spillage in Nigeria.  
Vigorous upstream and downstream activities in this region have led to an enormous 
environmental contamination over the years. The environmental problems of the 
Niger delta are complex, interconnected and caused by many factors (SNAR, 2005). 
3 
 
 
Although environmental degradation also arises from natural sources, the most 
common environmental problems in the region results from oil spills, gas flaring, 
construction of oil facilities, pollution from industries and dredging of canals (Oil for 
Nothing, 1999).  
Aside the Niger Delta communities, several communities have experienced oil 
spill due to vandalized pipelines in recent times, most of these spills are left without 
clean up measures.  
   1.3 Remediation of petroleum contaminated sites 
There are various works focused on the remediation of petroleum polluted sites 
and some common methods of clean–up are used. These methods include 
engineering (excavation, transportation and incineration of the contaminated soi ; ex-
situ)), pump-and–treat, soil vapour extraction, sparging and chemical washes (in- 
situ) (Cunningham et al, 1995) and more environmentally friendly bioremediation. 
Bioremediation mostly involve use of micro- organisms like bacteria, fungi and 
protozoa to degrade contaminants into less toxic or non-toxic compounds                   
(Pierzynski et al, 1994).  
Bioremediation technology exploits various naturally occurring mitigation 
processes: natural attenuation, biostimulation and bioaugmentation. With natural 
attenuation, remediation occurs without human intervention other than monitoring. 
Biostimulation is the use of indigenous microbial populations to remediate 
contaminated soils and involves adding nutrients and other substances to soil in order 
to catalyze natural attenuation processes. Bioaugmentation involves introduction of 
exogenic microorganisms (sourced from outside the soil environment) capable of 
detoxifying a particular contaminant, sometimes it employs genetically altered 
microorganisms (Biobasics, 2006).  
The use of plants in remediation is referred to as phytoremediation while the 
use of animals in remediation is referred to as zooremediation (Cunningham et al, 
1995). Although the uses of various plants for remediation are well reported, fewer 
reports are available for the use of animals. Phytoremediation involves exploiting 
plant's natural ability to contain, degrade, or remove toxic chemicals and pollutants 
from soil or water. It can be used to clean up metals, pesticides, solvents, explosives, 
4 
 
 
crude oil, and contaminants that may leak from landfill sites. Several plants such as 
sunflower, ragweed, cabbage and geranium, as well as other less known species are 
known phytoremediants. The plants are often used in combination with other 
traditional technologies for cleaning up contaminated sites because of the 
phytoremediation's limitations. Zooremediation mostly involves biostimulation 
process; the animals‟ actions improve the environmental conditions of the site and 
thereafter influence the activities of microorganisms. This is a less researched area; 
however some investigations involving earthworms and other invertebrates indicates 
that animals play a role in enhancing the activities of microorganism and hence could 
be exploited for bioremediation (Zachery and Reid, 2008b; Sinha, et al, 2010). 
Earthworm based technology has proved commercial potentials as the role of 
earthworms in the conversion of organic materials and improvement of soil has been 
observed and appreciated (Biobasic, 2006; Zachery and Reid, 2008a). 
  1.4 Earthworms 
Earthworms are detritus feeders occupying a notable position of producer in the 
terrestrial food chain. They are hardy organisms capable of surviving highly toxic 
environment, for instance, it was the only survival soil fauna after the 1976 Seveso 
chemical plant explosion in Italy (Satchell, 1983).  
Earthworms belong to the class annelida, Annelids have cylindrical body which 
is segmented both outside and inside. They are invertebrate organisms found in 
marine, freshwater, as well as brackish and arboreal environments, seashore and 
terrestrial habitats; they may be pelagic, surface dwelling, or benthic, burrowers or 
tube dwellers, mobile or sessile. There are approximately 4500 identified species of 
worms in the world, about 2500 are earthworm species and more than five hundred 
species of earthworms have been identified in India (Kale and Karmegam, 2009). 
Lavelle, 1978, had reported the earthworm density for western Africa as 0.1–4.0 
million worm/ha and in European soils as 2.5–9.5 million worms/ha. Owa et al., 
2002 reported the earthworm density in their study of earthworm density and 
diversity across ecological zones Nigeria as 0.85 million worms/ha. He also reported 
the species of earthworms in the ecological zones as Ephyriodrilus afroccidentalis, 
Eudrilus eugeniae, Hyperiodrilus africanus, Parapoly-toreutus obiensis, 
5 
 
 
Eminoscolex steindach-neri, and Libyodrilus mekoensis in same report. The 
ecological zone secondary forest had the highest diversity of earthworms in Nigeria. 
The life span of earthworms range between 3 to 7 years depending on the species and 
the environmental factors; they are known to produce 300-400 young earthworms 
during their life cycle (Hand, 1988). The average temperature range suitable for their 
0 0
survival is 20 C – 25 C while their optimum moisture ranges between 60-75%. 
Earthworms are either earthmovers or composters. Earthmovers tend to be 
solitary species which tunnel through the earth, aerating, decompacting and mixing 
soil strata and thus making surface nutrients available to plant roots at lower levels. 
(Kale and Kaomagma, 2009). Earthworms are key organisms in (environmental) 
toxicology; it was identified as a model organism for assessing the effects of 
chemicals on terrestrial saprotrophic invertebrates. (OECD, 1984).  
 1.5 Research rationale  
Oil spillages have far reaching implications on the socio-economic well being 
of the people. The numbers of petroleum contaminated sites are on the increase in 
Nigeria, most of such sites are not assessed to determine the extents of pollution 
hence are neglected even if they need clean-up. The Nigerian government and oil 
companies are either slow or insensitive. The Agaye community, in Lagos state 
Nigeria is one of such sites that have experienced repeated oil spill that resulted to 
th
inferno as reported in the Punch, 29  Dec, 2006. No baseline records are available 
on the physicochemical parameters of soil and water in this area. Investigation to 
estimate the extent of contamination and researches geared towards remediation 
using locally available materials and environmentally friendly measure for site 
reclamation is therefore necessary.  
Based on the foregoing premise, this study involved empirical estimation of the 
extent of contamination in Agaye soil and water. It also involved the estimation of 
the earthworm species diversity and abundance after the petroleum spill and 
determining the role of the most abundant and most tolerant indigenous earthworm 
species in bioremediation of the soil. 
 
6 
 
 
1.6 Aim and Objectives 
This study aimed at determining the levels of petroleum contaminants in the 
soil and water in the oil spill area of Agaye and the impact of the spill on the 
population of earthworms.  
              The specific objectives were therefore to evaluate the;  
i. physiochemical status of surface and underground water. 
ii. physicochemical status of the soil within the oil spill area in Agaye.  
iii. abundance and species diversity of the earthworm population in the study  
area 
iv. accumulation of heavy metals by the indigenous earthworms. 
v.  role of the indigenous earthworms in the remediation of the soil.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7 
 
 
                                                      CHAPTER TWO 
2.0                                          LITERATURE REVIEW 
            2.1       Pollution 
 
Man‟s health, his physical and psychological development are intimately 
associated with the natural conditions of the environment but pollution remains a 
major stress on the environment and causes changes which are deleterious to life. 
Pollution according to GESAMP (1991) is “any alteration of the chemical, physical 
or biological quality of the environment which results in any unacceptable 
depreciation which adversely and unreasonably affects its subsequent beneficial 
uses”. Environmental pollution refers to any unwanted change in the quality of the 
earth that is caused by the introduction, either by natural events or human activities, 
of substances in quantity and duration, which harm the health of living organisms or 
damage materials. 
Man‟s continuous advance in science and technology has caused severe 
environmental changes which are very difficult to evaluate and fully comprehend. 
Some of these activities result in the interference in nature which cause imbalance 
and displacement of ecosystem‟s linkages and relationships and may markedly 
reduce the system‟s life supporting capabilities. Pollution could result in chronic 
damage to water, air or soil.  
The atmosphere comprises of a complex mixture of gases and it provides the gases 
required for life‟s vital biochemical process. It acts both as an insulating blanket, 
maintaining life-supportive temperature range on earth and as a shield, reducing or 
blocking radiation from space that would otherwise be lethal to most life-forms. 
(Umolu and Aemere,1999). Pollution is occurs as a result of increasing human 
population, increasing industrialization with accompanying concentration of 
population into conurbation, (Adeyemo, 2003). The resultant effects range from 
direct or indirect impact on the health of living organism, acid rain falls (which 
affects the soil and water pH), perforation of the ozone layer and the resultant global 
warming which produces conditions threatening the survival of living organisms. Air 
pollution due to the release of isocyanate from the union carbide plant had been 
reported at Bhopal, India which led to the death of over 2,000 people in 1984 (Naik, 
et al, 1986) . The atmosphere habours a lot of pollutants such as metals, pesticides, 
8 
 
 
asbestos, radioactive materials, in particulate form and most reach the aquatic system 
as fall out (FAO/SIDA 1977; GESAMP, 1991). 
Water bodies, especially surface water are prone to pollution as they serve as 
repositories of run-offs from their surrounding environment. Apart from direct 
damage due to contact with and ingestion of water polluted by pathogens and other 
toxic substances, incalculable damage is done to life in water bodies. Basically, the 
hydrological conditions of a water body are very vital when assessing its 
productivity and other characteristics (Adebisi, 1981). In water bodies, important 
elements among others include nitrogen, phosphorus and oxygen. Nitrogen and 
phosphorus occur normally in low concentrations which are almost entirely 
consumed by routine plant physiological activity; excess amounts of these elements 
remain in the environment as pollutants. Furthermore, the survival of many fish 
species requires 3-4mg of dissolved oxygen per litre of water (Hamilton and James, 
1976), with limited amount, the survival of fishes is jeopardized and putrefaction 
phenomena becomes encouraged.  
Industrial and agricultural activities are major sources of pollutants. Industries are 
varied and diversified and so the nature of their operations and products. Thus 
different pollutants could be generated by any one industry depending on the level of 
industrial technology in use and the control measures adopted the significant impact 
of the different source types vary from one country to another, (Osibanjo, 1986), 
hence it is difficult to estimate the quantity of pollution a particular source would 
contribute. Agricultural sources contribute through run-off, from cultivated land, 
fertilizers and pesticides used on farm lands. It also contributes a lot of organic 
waste, although its contribution to pollution is a small fraction of the total pollutants 
getting into the aquatic habitats. Agricultural sources discharge over a geographical 
area, thus restriction of most of its pollutants is difficult (Osibanjo, 1986). Natural 
radioactivity and bush burning are other sources of pollution which results in 
radioactive pollution (Asamoah, 2013) and contribution of organic wastes 
respectively while weathering of rocks erodes constituent minerals, these finally 
reach the aquatic system through under-ground water or runoffs. Other pollutants 
common in water are heavy metals (like lead and mercury) and phenols. They are 
known to be absorbed and concentrated in the tissue of aquatic organisms thus 
9 
 
 
entering into the human food chain resulting in bioaccumulation and 
bioconcentration. Soil provides the base for virtually all human activities, settlements 
and it sustains the existence of plants and animals in general. Soils have large 
holding capacity for pollutants and acts as a long-term sink and major repository of 
contaminants in the environment (Wild and Jones, 1995). Plants absorb contaminants 
and serves as a route to the food chain and some contaminants percolate into ground 
water systems and eventually to surface water.  
Petroleum occurs in nature and normally seeps into the environment (Stones and 
Seager, 1979). The exploitation, production and marketing of crude oil have very 
remarkable effect resulting in extensive damage to aquatic life, impairment of 
recreational value of beaches, losses in fisheries and rejection of aquatic food 
resources by the public and changes in water quality (Umolu and Aemere, 2000). 
Etkins, 2001 described “oil spill” as events where oil is discharged accidentally, due 
to neglect or intentionally for a short period but neither slow oil leaks for a long 
period nor operational discharge. 
  2.2   Petroleum 
Petroleum is generally described as a complex mixture of hydrocarbons (having 
molecules of only carbon and hydrogen, mostly alkanes) and non hydrocarbons 
molecules such as nitrogen, sulphur, and oxygen. The elemental compositions and 
appearance of petroleum vary greatly in various crude oil types. Petroleum is usually 
found in porous rock formations in the upper strata in some areas of the earth‟s crust 
(Timmis et al., 1998). 
There are two schools of thought regarding the origin of petroleum: a western 
school suggesting that its origin is biogenic (biotic) resulting from the decay of 
organic biological matter and stored in sedimentary basins near the earth‟s surface 
and an Ukrainian – Russian school proposing that the origin is abiogenic (abiotic) 
with inorganic origin deep within the earth‟s crust dating back to the creation of the 
earth. The issue of the origin of petroleum remains a controversy between the two 
schools of thought, however, that of biogenic formation remains the most widely 
accepted theory. Its formation involves a slow breakdown process, known as 
diagenesis, which produces a range of hydrocarbons and hydrocarbon complexes 
10 
 
 
significantly altered from the structure found in the original biomass (Aigeson, 
1996). The process involves the physical, chemical or biological alteration of 
sediments into sedimentary rocks at relatively high temperatures and pressures that 
can result in changes to the rock's original mineralogy and texture (Marfil et al., 
1998).  
Petroleum hydrocarbons are organic compounds which are known to arrange in 
varying structural configurations. Crude oil hydrocarbons are divided into two 
families, aliphatics (fatty) and aromatics (fragrant). Crude oil and refined petroleum 
products contain four major groups of hydrocarbons: alkanes, olefins, alicyclics, and 
aromatics.  
     2.2.1 Constituents of petroleum 
 
 The main elements of petroleum are combined to form a complex mixture of 
organic compounds that range in molecular weight from 16 (methane; CH4) to 
several thousands. A wide range of metals are also found in trace amounts in crude 
oil. All metals through the atomic number 42 (molybdenum) have been found, with 
the exception of Rubidium and Niobium; a few heavier elements also have been 
detected. Nickel and Vanadium are the most important, because they are present in 
all crudes, usually at concentrations far higher than any other metal (Ali and Abass, 
2006). Organic compounds containing sulfur, nitrogen and oxygen may be 
encountered at significant concentrations in crude oil and in some heavier fuels such 
as No.6 fuel oil.  
Some other components of petroleum apart from hydrocarbons can be grouped 
under asphaltenes and resins, polar and porphyrin constituents. Asphaltenes and 
resins makes up a large fraction of crude oils and heavy fuel oils, making those oils 
very dense and viscous. Asphaltenes are substances in petroleum that are insoluble in 
solvents of low molecular weight such as pentane or hexane and they are solids at 
normal temperatures. Oils that have high asphaltene contents are very viscous, with 
high pour point and are generally nonvolatile in nature. The porphyrins, asphaltene, 
and resin compounds are considered the residual oil, or residuum. During the 
weathering process, this fraction is the last to degrade, and its persistence over years 
is known. Other constituents include porphyrins, which are complex large cyclic 
11 
 
 
carbon structures derived from chlorophyll and characterized by the ability to contain 
a central metal atom (trace metals are commonly found within these compounds).  
     2.2.2   Petroleum production 
 
 The processes involved in the petroleum industry include exploration, drilling, 
extraction, refining and transportation / distribution. Oil exploration is the act of 
searching for crude petroleum in the ground, either onshore or offshore. As the 
search has become increasingly difficult, the industry has moved to more 
sophisticated detection techniques (Surdam, 1997). Airplanes and satellites make 
remote sensing possible, using a combination of photography, radar, infrared 
imagery, microwave frequency receivers and other technologies to identify possible 
production areas and to predict the likelihood of significant reserves (Beaumont and 
Foster, 1992).  
Once oil and gas is found, development begins with the drilling of 10 to 30 
wells per platform. Since more wells are drilled during development than during 
exploration, a larger volume of drilling mud and cuttings is discharged in this 
process. Once the drilling unit used in development is removed, extraction of 
hydrocarbons from the underground formation begins (Menzie, 1983). 
Offshore oil platforms produce a wide variety of liquid, solid and gaseous 
wastes, some discharged directly into the ocean. Onshore oil production operations 
produce quantities of cuttings and mud, ranging from 60,000 to 300,000 gallons per 
day, while offshore oil platforms use nearly 400,000 gallons of water per day, 
released directly into the ocean. Lined pits for disposal are sometimes used in 
association with land rigs, but mud, drill cuttings, and other materials are often 
discharged into the ground (Guidotti, 1995). Some extraction techniques require the 
use of sub-surface explosives, or „torpedoing‟ to breach certain geologic features. Oil 
and gas exploration and drilling are the most hazardous sectors of the oil industry  
When extraction is completed, crude oil is transported to an oil refinery where 
complex hydrocarbon compounds are separated, converted, and treated, becoming 
useable fuel sources. The process of refining oil manufactures nearly 2,500 useful 
products (Gennaro et al., 2000) but the major end product of oil is gasoline, followed 
12 
 
 
by diesel fuel, jet fuel, fuel oils, kerosene, lubricating oils, and asphalt used for road 
paving (Oduntan, 2000). 
Commercial petroleum hydrocarbons are produced through distillation of crude 
oil. In general, the lighter fractions represent gasoline-range material. The 
intermediate or middle distilled fractions represent feedback for diesel, jet fuels, and 
light heating oils. The residuum in this process serves as heavy fuel oils or other non-
fuel products (Nyer and Skladany, 1989; Potter, 1992). Table 2.1 indicates some of 
the major commercial products associated with different distillation fractions. 
Gasoline, diesel, and fuel oils are the most common petroleum products 
contaminating soils and groundwater because of their widespread usage, (Block, 
1991).  
Robust technology has emerged to move (transport) extracted crude oil from point of 
extraction to oil tanks from where it is further transported through pipes to refineries. 
This technology involves the use of ships and pipelines to transport extracted oil. 
Refined products also need to be moved to myriad distribution points which are 
made possible by the immense networks of pipelines. Pipelines are highly pressured 
conduits for the transfer of large volume of oil, varying in width and carrying 
capacity. Pipelines are able to function 24 hours in a day, under any weather 
conditions, hence they are preferred. They are prone to corrosion and burst relatively 
frequently due to faulty equipments, human error and intervention. These often lead 
to spills and fires posing serious threats to neighbouring populations and surrounding 
environments. The life span of a pipeline is acknowledged to be 15 years (Borasin et 
al., 2002). 
               2.2.3 Major petroleum products 
 
Gasoline is a mixture of volatile hydrocarbons suitable for use in internal combustion 
engines. The major chemical components of gasoline are branched chain paraffins 
(branches chain alkanes), cycloparaffins (cycloalkanes), and aromatics. The 
composition of gasoline may vary depending upon the origin of the crude oil, 
differences in processing and the incorporation of various additives to improve 
performance. Common additives include: metals such as alkyl lead; 
13 
 
 
          Table 2.1  Petroleum Distillation Products 
 
 
Fraction Distillation Carbon 
 
Temperature Number 
o
C 
   
Gas Below 20 C-1 to C-4 
   
Petroleum 20 to 60 C-5 to C-6 
ether 
   
Ligroin (light 60 to 100 C-6 and C-7 
Naphtha) 
   
C-5 to C-10 
Natural 40 to 205 
and 
Gasoline Cycloalkanes 
   
C-12 to C-18 
Kerosene 175 to 325 
and 
Aromatics 
   
Gas Oil Above 275 C-12 and 
higher 
   
Probably long 
Lubricating Non-volatile 
chains 
Oil liquids attached to 
cyclic 
compounds 
   
Asphalt or 
Non-volatile Polycyclic 
Petroleum 
Coke solids structures 
 
             Adapted from Morrison and Boyd (1973). 
14 
 
 
oxygenates such as ethanol, methanol, methyl tertiary butyl ether (MTBE), tertiary 
butyl alcohol (TBA), tertiary amyl methyl ether (TAME), and ethyl tertiary butyl  
ether (ETBE); additional aromatic hydrocarbons such as benzene, toluene and 
xylene; and others including ethylene dibromide (EDB), ethylene dichloride (EDC), 
and methyl cyclopentadienyl manganese tricarbonyl (MMT) (Caprino and Togna, 
1998). These varieties of additives are meant to improve engine performance. 
Methyl tertiary-butyl ether (MTBE) is found in many drinking water wells, but 
mostly at levels below that known to cause human health effects.  
Diesel is Number 2 Fuel Oil, composed primarily of unbranched paraffins 
o o
(straight chain alkanes) with a flash point between 110 and 190 F (43 and 88 C).  
Diesel is largely comprised of simple un-branched n-alkanes, with only around 4% 
of polyaromatic compounds (Heath et al 1993). Fuel oils are generally chemical 
o o
mixtures having flash points greater than 100 F (38 C). Fuel oils can be distilled 
fractions of petroleum, residuum from refinery operations, crude petroleum, or a 
mixture of two or more of these materials. 
Petroleum is also the raw material for many other chemical products, including 
solvent, fertilizers, pesticides, and plastics. Most of the petroleum extracted is 
processed as fuels, including gasoline, diesel, jet, heating, and other fuel oils, and 
liquefied petroleum gas; the other is converted into other materials such as plastic. 
  2.3 Petroleum pollution and its ecological effects 
The pollution problems caused by oil industries are extensive ensuing from 
exploitation, production and marketing of crude oil. These have very remarkable 
effect including extensive damage to aquatic life, impairment of recreational value of 
beaches, losses in fisheries and rejection of aquatic food resources by the public and 
changes in water quality (Umolu and Aemere, 2000). Dating back to World War II, 
the use of petroleum products became common and there was a shift from the use of 
coal for the generation of energy in most economy (Onwurah, et al., 2007). The 
volume of crude oil or petroleum products that is used today cannot be compared to 
all other chemicals of environmental and health concerns. Due to the number of 
facilities, individuals involved, processes and the various ways the products are 
stored and handled; environmental pollution and contamination associated with 
15 
 
 
petroleum is potentially widespread. Petroleum occurs in nature and normally seeps 
into the environment (Stones and Seager, 1979). Etkins, 2001 described “oil spill” as 
events where oil is discharged accidentally, due to neglect or intentionally for a short 
period but not slow oil leaks for neither long periods nor operational discharge. 
In the year 2003, worldwide crude oil production volumes surpassed 82.3 
million barrels per day and this volume is estimated to increase to 94.3 barrels per 
day in 2010 and 101.6 barrels per day in 2015 (US DOE/EIA, 2006). Improper 
management and disposal has often led to environmental pollution, particularly of 
the soil and groundwater systems due to the chemical complexity of petroleum. 
A lot of petroleum pollutants are introduced by accidental discharge of oils from 
loaded vessels on seas, other common routes include:  
I      Flow-line / pipeline leakages and rupture. 
II     Corrosion of flow-lines or pipelines 
III    Over pressure of pipelines 
IV    Valve failure 
V     Hose failure 
VI   Collision and grounding of tankers. 
During exploration and production activities, accidental spills occurs e.g. blowout 
from off-shore, oil drilling and production. Spills can also occur during transportation 
and supply operation. Over 25 million barrels of oil spill reported worldwide since 1980, 
mostly in small quantities (<7 tonnes) occurring frequently from bunkering, routine 
discharge and loading of tankers, and larger spills (< 700 tonnes) occurring 84% of the 
time due to accidental causes (ITOPF, 2006).  The international oil and gas pipelines 
running through several million kilometers on land and water bodies serve as potential 
points of spills as these pipelines are subject to wearing overtime (Beller, et al. 1996). 
Oil spill with worldwide attraction include the Torrey Canyon spill in 1967; wherein 
hundreds of kilometers of the southern England coasts and the Brittany region of France 
were polluted by oily mousse, this resulted in the fouling of organisms with petroleum 
residuum. Ecological damages also emanated from the clean-up chemicals used resulted 
in the death of 30, 000 seabirds (Harvey, 1997). Consequently, this affected their 
population size for several years after the incidence. The aftermath effect of the 
detergents and dispersant used for this clean-up however brought to limelight the need 
16 
 
 
for judicial consent as regards choice of clean-up materials as well as the amount to be 
applied. One of the largest oil spills in the 1970‟s was the Amoco Cadiz oil spill in 1978. 
There was an estimated 223, 000 tonnes of oil spilled with the number of birds mortality 
as 300, 000 (Godson et al, 2009). The Exxon Valdez accident which occurred in North 
American waters in 1989 recorded an estimated 37,000 tonnes of oil spilled and an 
estimated 350,000 seabirds were reported dead (Short, et al. 2002; Oil Spill Intelligence 
Report, 1999). A number of other oil spills of large sizes, caused little or no 
environmental damage and did not impact coastlines because they occurred several 
kilometers offshore (ITOPF, 2012). However, the claim of no environmental damage 
might be untrue as this assertion is likely due to difficulty in the evaluation of 
environmental impact such distances offshore. 
Earlier reports from 1993 to 2002 indicated no correlation between the size of an oil 
spill and the number of estimated seabird mortalities however findings from Tan et al., 
2010 indicated that oil spills <50,000 tonnes, had strong correlation between oil spill 
size and estimated bird mortality but not with larger spills (100, 000-225, 000 tonnes).  
The 2010, BP oil spill in the gulf of Mexico is one recent spills which attracted 
international interest, during this spill, > 200 million gallons of oil poured into the Gulf 
of Mexico followed by 1.8 million gallons of dispersants used for clean-up (Repanich, 
2010)  
Petroleum refineries are major sources of hazardous and toxic air pollutants 
such as BTEX (benzene, toluene, ethylbenzene, and xylene) compounds. They are 
also a major source of air pollutants like particulate matter (PM), nitrogen oxides 
(NOx), carbon monoxide (CO), hydrogen sulfide (H2S), and sulfur dioxide (SO2).                                                                                                                                              
Refineries also release less toxic hydrocarbons such as natural gas (methane) and 
other light volatile fuels and oils (Anderson et al., 1998; Epstein and Selber, 2002). 
Oil production contributes to air pollution in form of flaring, burning of natural gas 
extracted along with crude oil. Worldwide gas flaring contributes 35 million tons of 
carbondioxide and 12 million tons of methane contributing greatly to global 
greenhouse effect. Gas flares release smoke into the atmosphere which contributes to 
rising amount of acid rain (Moffat and Linden, 1995). 75% of natural gas i.e. by-
product of oil extraction has been flared in Nigeria covering the surrounding with 
black soot. For Saudi Arabia ; 20%, Iran 19%, Mexico 5%, Britain 4.3%, Algeria 
17 
 
 
4%, former Soviet union 1.55, U.S. 0.6%, Nertherland 0% (Epstein and Stilber, 
2002).   
Contamination of soils from the refining processes is generally a less 
significant problem when compared to contamination of air and water. Post 
production practices may have led to spills on the refinery properties that now need 
to be cleaned up. Natural bacteria that may use the petroleum products as food are 
often effective at cleaning up petroleum spills and leaks compared to many other 
pollutants. Many residuals are produced during the refining processes and some of 
them are recycled through other stages in the process. Other residuals are collected 
and disposed of in landfills, or they may be recovered by other facilities. Soil 
contamination including some hazardous wastes, spent catalysts or coke dust, tank 
bottoms, and sludges from the treatment processes can occur from leaks as well as 
accidents or spills on or off site during the transport process. Many refineries go to 
great lengths to treat or filter petroleum waste in order to prevent environmental 
damage. Water used in refining process must be treated to remove traces of heavy 
metals, noxious chemicals, solvents and residual aromatic hydrocarbons before this 
water can be released into disposal wells or waterways (Epstein and Selber, 2002). 
Oil refineries also contribute other forms of pollution like thermal pollution of water 
body which disrupts surrounding marine ecosystems. 
Generally, when petroleum products are released into the environment, 
changes occur that significantly affect their potential effects. Physical, chemical, and 
biological processes affect the location and concentration of hydrocarbons at any 
particular site. The ultimate environmental exposure to petroleum products is 
determined by how the product changes with use, by the nature of the release, and 
the hydrocarbon‟s environmental fate. 
  2.4 Health effects of petroleum pollution 
Some of the chemicals released during petroleum contamination are known or 
suspected cancer-causing agents, responsible for developmental and reproductive 
problems. They may also aggravate certain respiratory conditions such as childhood 
asthma. Along with the possible health effects from exposure to these chemicals, 
these chemicals may cause worry and fear among residents of surrounding 
18 
 
 
communities. Air emissions can come from a number of sources within a petroleum 
refinery including: equipment leaks (from valves or other devices); high-temperature 
combustion processes in the actual burning of fuels for electricity generation; the 
heating of steam and process fluids; and the transfer of products. Many thousands of 
pounds of these pollutants are typically emitted into the environment over the course 
of a year through normal emissions, fugitive releases, accidental releases, or plant 
upsets 
The primary component of concern in the BTEX complex is benzene, which has 
been classified as a known human carcinogen by the U.S. Environmental Protection 
Agency (USDHHS, 1993).  
   2.4.1  Benzene 
 
Acute benzene exposure causes central nervous system depression, irritation to 
the eyes and respiratory tract while continued exposure may cause euphoria, nausea, 
staggering gait, and coma. Inhalation of lower concentrations causes vertigo, 
drowsiness, headache, and nausea. Chronic exposures to benzene induce well-
recognized hematotoxicity, especially bone marrow suppression. Benzene has an 
odor threshold in water of 2.0 ppm, and a taste threshold of 0.4-4.5 ppm. The EPA 
maximum contamination level (MCL) of benzene in drinking water supply is 5.0ppb. 
EPA recommends a short-term (10 days) advisory level for benzene in water at 200 
ppb for children. The Occupational Safety and Health Administration (OSHA) 
permissible exposure limit (PEL) in the workplace for benzene is 1.0ppm (OSHA, 
2010). Benzene is the most water soluble fraction of the BTEX complex with 
solubility of 1780 mg/L (Irwin, 1997) it is usually found to be in the highest 
concentration in petroleum contaminated water.  
     2.4.2 Toluene 
Toluene is usually found in gasoline, paints, paint thinners, adhesives, 
fingernail polish, and other petroleum-based products. It has an odor threshold of 
2.14 ppm in air. Acute adverse health effects from exposure to toluene include 
headache, confusion, and memory loss, depending on the concentration, duration, 
and route of exposure. Brief exposure to a concentration of 100 ppm causes central 
19 
 
 
nervous system dysfunction. Exposures to 500 ppm to 800 ppm cause progressively 
increasing headache, drowsiness, nausea, fatigue, weakness, and confusion. Toluene 
also may interact with some common medicines like aspirin and acetaminophen to 
affect hearing (Irwin, 1997). Ingestion of toluene-contaminated drinking water may 
temporarily affect the kidneys. In most cases, the kidneys will return to normal after 
the exposure stops. The EPA MCL for toluene in drinking water is 1.0 ppm. The 
EPA Health Advisory for “toluene in drinking water for children is 20 ppm for 1 day 
and 2.0 ppm for 10 days” (EPA, 1997).  The OSHA PEL for toluene in the 
workplace is 200 ppm. Studies in workers and animals exposed to toluene indicate 
that toluene has not been shown to cause cancer (OSHA, 2010) 
   2.4.3 Ethylbenzene 
Ethylbenzene is a colorless liquid that smells like gasoline, with an odor 
threshold of 2.0 ppm in air. It occurs naturally in coal tar and petroleum, and it is 
found in paints, inks, carpet glues, varnishes, and insecticides. Gasoline contains 
about 2% ethylbenzene. Ethylbenzene is an irritant of the skin and mucous 
membranes. At high concentrations, it causes narcosis in animals. Humans briefly 
exposed to 1,000 ppm experienced eye irritation, but tolerance develope rapidly, 
exposure at 2,000 ppm caused lacrimation, nasal irritation, and vertigo. Ethylbenzene 
is also an irritant to the skin and mucous membranes and a high concentration can 
possess narcotic properties (Fishbein, 1985).  
Exposure at 5,000 ppm produced intolerable irritation of the eyes and nose 
(ACGIH 1991) while sleepiness, headache, and mild irritation of the eyes and 
respiratory tract were reported from chroni exposure of 100 ppm (Hathaway et al. 
1991). Studies to date indicate that ethylbenzene is neither carcinogenic nor 
teratogenic in humans (NTP-TR, 1999, USEPA, 1991). The EPA MCL for 
ethylbenzene is 0.7 ppm. The EPA Health Advisory for ethylbenzene in drinking 
water is 30 ppm (1 day - child) and 3.0 ppm (10 days - child), and a lifetime advisory 
for adults of 0.7 ppm. The OSHA PEL for ethylbenzene in the workplace is 100 ppm 
(OSHA, 2010) 
20 
 
 
   2.4.4  Xylene 
Xylene is a colorless liquid with a sweet odor. Xylene has an odor threshold of 
about 2.2 ppm in water. Xylene exists in three forms: meta-xylene, ortho-xylene, and 
para-xylene. Chemical industries produce xylene from petroleum, and it is found 
naturally in petroleum and coal tar. Xylene vapor is an irritant of the eyes, mucous 
membranes, and skin; at high concentrations it causes narcosis. Air levels of 60 ppm 
to 350 ppm have produced giddiness, anorexia, and vomiting. Volunteers exposed to 
460 ppm for 15 minutes had a slight tearing and lightheadedness (Chen, et al., 1994). 
A level of 230 ppm was not considered to be objectionable to most of these same 
volunteers. Exposure of pregnant women to high levels of xylene may be teratogenic 
and cause harmful effects to the fetus (Donald et al., 1991). Studies of unborn 
animals indicate that high concentrations of xylene may cause an increase in the 
number of deaths, decreased weight, skeletal changes, and delayed skeletal 
development (USDHHS) Data from animal studies indicate that xylene is not 
carcinogenic. The EPA MCL for total xylenes in drinking water is 10.0 ppm. The 1-
day, 10-day, and longterm EPA Health Advisory for children exposed to xylene is 40 
ppm. The Health Advisory for long-term exposure in adults is 100 ppm. The OSHA 
PEL for xylene in the workplace is 100 ppm. 
   2.4.5 Metals                                                                                           
Metals are constituents of petroleum found in the porphrin complex of crude 
oil (Barwise, 1990) although at low concentrations, some of these metals are of 
health importance. Lead, manganese, copper, cadmium, zinc, chromium, nickel and 
vanadium are some of these metals. Among these metals, nickel and vanadium are 
known parameters diagnostic for petroleum type (Barwise, 1990 and Filby, 1994). 
   Lead is used as an additive in gasoline; it is an antiknock agent for automobile 
engines and it improves the octane quality of the product. The use of lead as 
antiknock agents dates back to 1921 when it was discovered by Midley (Mc Grayne, 
2001, Kovarik and Charles, 1994, Steinberg, 2009) but its use became popular in the 
1970‟s. This led to the increased levels of lead found in urban areas. Although, the 
use of leaded fuel has been banned in most developed countries, it is still in use in 
21 
 
 
some undeveloped countries. This is because other alternative antiknock agents are 
more expensive than lead. Other major sources include natural weathering and 
painting rinds, (WHO, 1993). The ban in its use as antiknock agent was due to 
numerous health implications associated to lead.  
 20 to 30% of human lead poisoning is attributed to water sources majorly 
when leaded pipes are used in old building and as coatings in some ceramic plates 
and cups; other sources include food and air (Brown and Margolis, 2012). Lead levels 
in surface water and ground water are relatively low. Health implications from lead 
poisoning include impaired physical and brain development especially in infants and 
children below seven years of age (Reagan and Silbergeld, 1989), resulting in low 
attention span and learning rate indicated by a low IQ, 10µg/dl increase in blood lead 
level can be sufficient to cause this effect (WHO, 1993). In adults, high levels of lead 
could result in high blood pressure and kidney complications. The absorption of lead 
in the body depends on the route of the exposure and the part of the body absorbing 
the metal, however, 50% of lead is absorbed in children and pregnant women but 
only 15% is absorbed in adult. Other symptoms of lead poisoning include fatigue, 
insomnia, retarded development of feotus, hearing and vision impairment and 
decreased sperm count. The WHO limit of lead in drinking water is 0.01mg/L (WHO, 
2007) while the NESREA limit is 0.2mg/L (NESREA, 2010)  
  Manganese is a common metal found abundantly in nature, it is an essential 
element in all species and necessary for human survival (Jakubovis and Jenkinson, 
2001). The metal is needed in trace amount as it is a major constituent of some enzymes 
and bones. It is also needed in the functioning of the immune system, respiration, 
digestion and reproduction. Elevated amount of the metal can be toxic and is usually 
ingested as food (tea and herbs), manganese poisoning otherwise called manganism can 
develope into parkinson disease at later age (Spiegel-Ciobanu and McMillan, 2007). The 
symptoms include hallucination, forgetfulness, bronchitis and nerve damage. Chronic 
manganese poisoning can affect the central nevourse system. Outbreaks of manganese 
toxicity reported in Japan and Greece resulted from drinking well water with 1.8 – 14 
mg/l of manganese (Kawamaru et al., 1941 and Kondakis et al., 1989). Clinical cases 
associated with chronic ingestion of as low as approximately 1.2ppm of manganese have 
22 
 
 
also been reported (Aschner, et al., 2005). In the US, <0.05ppm is the recommended 
limit for drinking water while the WHO health-based value for manganese is of 0.4 mg/l 
while the acceptability threshold is 0.1 mg/l and NESREA drinking limits 0.2mg/L                                 
.           
Nickel is a hard silvery- white metal which occurs more commonly as iron-
nickel molten core. Nickel is easily absorbed by organic matter hence is found in 
relatively high amount in coal and crude oil. Soil nickel content could vary from 0.2-
450 ppm depending on the type of soils. It is naturally found in some plants (beans 
and tea). In nature it could be found combining with sulphur and arsenic. This metal 
can be bioaccumulated by plants like vegetables. Nickel is grouped as a carcinogenic 
element and exposure to high levels can cause dizziness, birth defect, heart disorder, 
respiratory irritant and chronic exposure could result in dermatitis. Nickel is known to 
bind to soil particles hence becoming immobile but in acidic soils it becomes mobile 
and can be rinsed into ground water. Nickel could be toxic and antangonistic to 
microorganisms but they can develop resistance.  
Cases of cancer around refineries are associated with nickel; it is also reported 
to affect the nervous system and the kidney (Gosselin, 1984). Athough, exposure to 
animals showed no carcinogenicity (Hathaway et al., 1991), positive mutagenicity 
was demonstrated in invitro test but not invivo. Acute exposure is known to cause 
nickel itch which is expressed in itching and swellings especially on moist skin 
(Hathaway et al., 1991). Nickel does not accumulate in fish or small soil fauna. 
Exposure of nickel to feotus is possible from mother to child and through breast 
feeding; higher concentrations of nickel have been found in processed baby milk of 
cow origin. Levels of nickel is usually low or not detectable in surface water like 
lakes and rivers but accidental exposure of nickel of upto 250ppm from contaminated 
water was reported to have caused stomach ache, increased protein in kidney and 
increased red blood cells. Chronic exposure led to bronchitis and reduced liver 
function in workers of refineries. WHO limit for drinking water is 0.07mg/L while 
the NESREA limit is 0.1mg/L  
Vanadium is and element usually found combined with a wide range of 
+2 +3 +4 +5
minerals or it can be found in various oxidation state (V , V , V  and V ). It is 
23 
 
 
also found in carbon rich deposit like coal, tar sand and oil shale hence its diagnostic 
role in oil spills (Fish and Komlenic, 1984), forest fires are also known sources of 
vanadium (Nriagu, 1990). It is used in producing alloys, although the ores of 
vanadium is known but it is not normally mined. The compounds of vanadium are 
highly soluble mostly in its monomeric forms hence it can easily be distributed by 
water. Vanadium is also found abundantly is soils and it can be accumulated by 
plants; the level of accumulation is an indication of its concentration in soil.  It 
concentration in soil ranges from 0.04 - 220µg/L based on the type of soil. 
Vanadium is an important component of some enzyme like the vanadium 
dehydrogenase in nitrogen fixing bacteria. There are no serious health implication 
associated with exposure to vanadium however severe eye, nose and throat irritation 
were observed in workers exposed to vanadium peroxide dust. Intake of food with 
vanadium is the commonest form of ingestion by humans. Heavy exposure to 
vanadium peroxide could result in bronchitis and pneumonia. Acute effects of 
vanadium pentoxide exposure include irritation of lungs, throats, eyes and nasal 
cavities Lees (1980). The particular symptoms expressed depend on the oxidation 
state of the vanadium exposed to individuals. Organisms like algae, plants and 
invertebrates bioaccumulate vanadium. Laboratory test on animals indicated impact 
on the reproductive system of male, lung cancer, anaemia, accumulation of the metal 
in the placenta, and DNA changes (WHO, 2006) however there are no proven 
evidence of being carcinogenic. 
Zinc occurs naturally as ore or stable isotope in the environment. Increased 
levels of zinc are as a result of release from industries during mining and processing. 
Zinc in high levels seep into ground water. Plants and fishes are known to absorb 
high levels of zinc. In the environment, high levels of zinc are found along side with 
cadmium and lead. Zinc is an essential element needed in both human and animals as 
it is play roles in the bone formation and in the functioning of enzymes like DNA 
and RNA polymerase. Lack of zinc can result in dermatitis, reduced reproductive 
capacity and retarded growth rate, increased feotal malformation (Cotran et al., 
1989), impacts on carcinogenicity (Fong et al., 1978).  
24 
 
 
Exposure is majorly through food although in small amount, beverages in 
metal cans and water which flows through zinc coated pipes are also sources of 
ingestion. A little amount is usually absorbed through skin. Chronic effect of 
ingestion of zinc could result in aneamia, central nervous system disorder while 
acute effect could include stomach cramp, nausea and vomiting. Exposure of zinc in 
the atmosphere had caused death in different incidences (Evans, 1945, Milike, et al., 
1963 and Hjortso, et al., 1988). It had also caused “metal fume fever” which is 
symptomized by impaired pulmonary function (Malo et al., 1990) and increased 
leucocytes (Blanc et al., 1991), nausea, abdominal discomfort and decreased number 
of red blood cells. 
Copper is a reddish metal that occurs naturally in the environment. It is a 
widely used metal in the industry and in agriculture. Increasing amount of copper is 
recorded in the environment with increased human activities like mining, phosphate 
ferlizer production and use of fossil fuel. Wind blown dust, forest fires and decaying 
vegetation are known natural sources (Davies and Bennett, 1985).  Copper binds 
with water sediments and soil particles, it is water soluble. Increased level of copper 
in drinking water could be attributed to the copper fittings in some plumbing 
systems; food, drinking water and atmospheric exposure are also known. Chronic 
effects include eye and mouth irritation, headaches, stomach aches, dizziness and 
aggravation of Wilson‟s disease. High levels of copper could cause decline in 
intelligence of adolescents, liver and kidney damage or even death acutely.  
Copper attaches to organic matter and minerals but hardly enters ground water, it 
is however fully mobile in surface water. Bioaccumulation in plants and animals occur 
affectingthe diversity of plants in soils with very high levels. Copper interrupts the 
activities of microorganisms and earthworms. Direct atmospheric exposure in males 
indicates toxicity to sperm; low motility counts (Battersby, et al., 1982). Examinations 
of CuSO,-poisoned animals showed signs of acute toxicity in the spleen liver and kidney 
(Clayto and Clayton, 1981), other symptoms of copper poisoning are shown by animals 
even at very low levels of its concentration like in sheep grazed on field with high 
copper contamination. Although the human body has a mechanism for maintaining the 
level of copper (Rutherford and Bird, 2004), this mechanism is not well developed in 
25 
 
 
children below 1 yr of age. Reproductive dysfunction, delayed growth and decreased 
litter have been observed in experimental animals exposed to copper (ATDSR, 2004). 
Cadmium is found naturally in the earth crust, sometimes in combination with 
zinc. Natural contamination is by weathering, forest fires and volcano. Human 
activities like manufacturing can also release cadmium. It is not mined but it is a by-
product from zinc extraction (ZnS) when cadmium sulphide is released. Cadmium 
can be ingested through food like liver and mushroom. Smoking of cigarette also 
increases cadmium level in the system. Inhalation of high concentration can result in 
severe damage of lungs. When absorbed, cadmium is hardly excreted through the 
kidney instead it destroys its filtering mechanisms. Other effects include diarrhea, 
bone fracture, nervous system and DNA damage and cancer development (ATSDR 
(2004). Cadmium flow from wastes to streams and end up in soils or air, artificial 
phosphate fertilizer plants also release cadmium. Earthworms and soil fauna are 
susceptible to cadmium poisoning causing their death at certain level however, 
bioaccumulation occur in aquatic ecosystem. High blood pressure, liver disease and 
brain damage are some of the symptoms of cadmium poisoning. 
The effects of individual constituents of petroleum are well documented and 
humans can be affected by oil spills from damage to surrounding plants and animals, 
and perhaps by direct contamination. One Scottish study found an increase nausea, 
headache, throat irritation and itchy eyes in local populations following spills, but 
long-term effects of this mixture are unknown (Borasin et al., 2002). Rigorous 
clinical studies are needed to assess the direct effects of oil spills on human beings 
  2.5 Oil Production in Nigeria  
The first obvious indication of oil resources in Nigeria dates back to 1908 with 
the appearance of oil at Araromi, in the present Ondo State. A German company, 
Nigeria Bitumen Corporation started this pioneering effort that was short-lived as a 
result of the outbreak of the 1914-1918 First World War. Another exploratory 
activity took off in 1937 by an Anglo-Dutch consortium that served as a forerunner 
of the present-day Shell D‟Arcy. The exploratory activity started in 1937 after Shell 
D‟Arcy had been awarded the sole concession rights that covered the whole territory 
of Nigeria. The company operated under the Mineral Oil Ordinance of No. 17 of 
26 
 
 
1914 and its amendments of 1925 and 1950 which allowed only companies 
registered in Britain or any of its protectorates the rights to prospect for oil in Nigeria 
and further provided that the principal officers of such companies must be British 
subjects. The 1939-45 Second World War interrupted the exploratory activities of 
Shell D‟Arcy.  
The Shell BP undertook the preliminary geological reconnaissance and 
intensified its geographical surveys from the 1946- 1951. It drilled its first wildcat 
well in 1951, which later dried up. Shell BP discovered its first commercial crude oil 
in the country in 1956 at Oloibiri in the present Rivers State (SNAR, 2005). That 
discovery ushered Nigeria into the international oil arena. Two years later (1958) 
Shell started oil exportation from Oloibiri field at a rate of 5,100 barrels per day. In 
order to increase the pace of oil exploration and to ensure that the country was not 
dependent on one oil company or nation, Shell‟s sole concession right over the 
country was reviewed and exploration rights were granted to companies of other 
nationalities. Oil companies like Mobil, Gulf, Agip, Safrap (ELF), Tenneco and 
Amoseas (Texaco/Chevron) were allowed to join the explorers for oil in the onshore 
and offshore areas of Nigeria. Having dug its first well in 1956, Royal Dutch/Shell 
now controls over half of Nigeria's oil production. When Nigeria gained 
independence in 1960, oil production had been established in the country and it was 
exporting over 170,000 barrels per day (bpd). It was Gulf Oil Company that first 
struck offshore oil on the Okan structure of Bendel State in 1964 being granted both 
offshore and onshore licenses. With these commercial discoveries in petroleum 
products, the socio-economic and political development of Nigeria began to 
crystallize as well as its internal dynamic ethnicity (NDES, 1997). 
    2.5.1 Nigeria oil refineries  
 
Once extracted, crude oil is transported to oil tanks from where it is further 
transported through pipes to refineries where it is refined to various useful products. 
Nigeria‟s total installed refining capacity is 445,000 barrels per day of crude oil, as at 
1990 to date. The three refineries in Nigeria are Kaduna refinery (KRPC), Port-
Harcourt refinery (PRPC) and Warri refinery (WRPC). 
27 
 
 
The Port-Harcourt refinery has 60,000 barrels per day processing capacity and 
was built by Shell-BP in 1964. It was taken over by the Nigerian government in 1977 
and became Nigeria‟s first refinery. The newest refinery having a processing 
capacity of 150,000 barrels per day which was initially designed as an export 
refinery has its location at the coastal village of Eleme, near the old Port Harcourt 
refinery. It is the most modern of Nigeria refineries and was commissioned in 1991 
(Nigerian crude oil and Gas, 2011). The Warri refinery has a processing capacity of 
125,000 barrels per day of crude. It has an adjoining petrochemical plant with 
production capacity for carbon black. It was built in 1978, with an initial capacity for 
100,000 bbl. per day, however it was de-bottlenecked in 1991 to increase processing 
capacity to 125, 000 bbl/day.  The Kaduna refinery was built and commissioned in 
1988 with processing capacity of 150,000 barrels per day. It has adjoining 
petrochemical plant which can produce asphalt, benzene and heavy paraffin base 
oils, used in the manufacture of vehicular lubricants and oils.  
The distribution of petroleum products conventionally involves pumping 
products through a crisscross of pipeline networks around the nation serviced by 
about twenty-one oil depots and the major terminals; Bonny, Qua Iboe, Brass, 
Forcados, Escravos, Pennington and Warri  (NDES, 1997). With the completion of 
the pipeline interlink project of 1994/95 (Pipeline Phase III), the length of the nations 
products distribution pipeline linking 20 storage complex increased to about 4950km 
(Adubi, 1995).  The complex is classified into 5 basic systems referred to as systems 
2A, 2B, 2C, 2D and 2E.  The Atlas Cove depot (a marine receipt terminal serving as 
a distribution and pump station for local and overseas refined products in Nigeria) 
marks the origin of the system 2B pipeline network of Petroleum Products Marketing 
Company Ltd. (PPMC) and is the largest petroleum products depot in Nigeria. It has 
3 3
a holding capacity of 114,300m  [Petrol – 48,000m , Dual Purpose Kerosene, DPK – 
3 3
34,000m  and Diesel (Automobile Gas Oil, AGO) – 32,300m ] (Adubi, 1995).  
Nigeria is the largest oil producer in Africa and the tenth largest in the world. The 
mainstay of Nigeria economy is the petroleum sector, contributing about 90% of the 
nation‟s foreign exchange earnings and about 25% of the Gross Domestic products. 
In 2006, its contribution to foreign exchange earnings reduced by 25% due the 
activities of the militant youths of the Niger –Delta (Leahy, 2006). A significant 
28 
 
 
proportion of the Nation‟s oil is produced onshore and is subsequently transported by 
pipelines, although recently oil production has witnessed increased activities in the 
offshore. The estimated national oil reserve is put at 35.2 billion barrel and average 
production of between 2.5 million barrel and 3.0 million barrel per day (bbl/d) 
(WAE, 2010)  
 2.5.2 Nigeria Oil spills and their ecological impact  
Although the quantity of oil drilling in Nigeria is small compared to that done in 
some other producing countries, lack of regulatory bodies and dependence on oil for 
income have led to sub-standard production operations. Oil pollution from normal 
operations including spills, accidents, leaks and waste discharges have caused 
significant ecological damage to the Niger - Delta. Vigorous upstream and 
downstream activities in this region have led to enormous environmental 
contamination over the years. The environmental problems of the Niger delta are 
complex, interconnected and caused by many factors (SNAR, 2005). Although 
environmental degradation also arises from natural sources, the most common 
environmental problems in the region results from oil spills, gas flaring, construction 
of oil facilities, pollution from industries and dredging of canals. (Oil for Nothing, 
1999) 
Shell Oil alone reported 130 spills in 1997; attributing 53 to equipment failure, 23 to 
human error and 54 to sabotage by those frustrated with the government and oil 
industry (NDES, 1997). According to Moffat and Linden (1995), at least 2300 cubic 
meters of oil from at least 300 spills contaminate the Niger Delta region annually. 
This is the "official" number reported. The actual amount of oil spilled annually 
"may be 10 times higher" (Moffat and Linden, 1995). In Nigeria, reports from 1976 
to 2001 showed that there had been 6,817 oil spills with approximately three million 
barrels of oil lost; an average of 273 oil spills and 115,000 barrels/year spilled in the 
Niger Delta alone (UNDP, 2006). However, Shell reported a total of 284,000 barrels 
of oil spilled and about 28,000 barrels year between 1990 and 2007 (SNAR, 2008). 
In a related report by IUCN/CEESP (2006), 9 to 13 million barrels of oil are claimed 
to be spilled into the Niger Delta ecosystem over the past 50 years. The discrepancies 
in the reports on the amount of oil spilled by oil companies operating in Nigeria and 
29 
 
 
world bodies like UNDP are indications that there are underestimated evaluations of 
oil wrecks caused by the operations of oil companies. It therefore calls for caution to 
out rightly depend on their reports of such spills and more international / national 
bodies and individual researchers with no affiliation to oil companies should be 
encouraged to investigate oil spills and there impacts when such occurs. Some 
notable oil spills recorded in Nigeria include Bomu 11 oil well blowout,1970, 
GOCON‟s Escravos spill, 1978 (300, 000 barrel), Forcados Terminal Spillage, 1980 
(580, 000 barrels), Oyakama pipelines spill (1980), Texaco Funiwa 5 blow out in 
1980 (400, 000 barrels), Abudu Pipeline Spill, 1982 (18,818 barrels), Ikata Pipeline 
Spill (1984), Okoma Pipeline Spillage (1985) and Oshika Pipeline Spill (1993), the 
massive Oloibiri Well 14 oil spill (2004), and very recently, Bodo oil spills (August 
2008 and February 2009) and K. Dere spill (April 2009), (Steiner, 2008). The 1980, 
Texaco Funiwa 5 blowout  was acclaimed as the worst oil spills in the 1980‟s with 
an estimated 200,000 barrels of oil spilled into the Atlantic Ocean and  a damaged 
340 hectares of mangrove (Nwilo and Badejo, 2005). Table 2.2 shows the total 
number of spill and volume of spilled between 1995 and 2013 in Nigeria by shell 
alone (SNAR, 2005).   
Other forms of pollution identified to be contributed by oil refineries include 
thermal pollution of water bodies. In Nigeria, oil pollution appears to be the major 
pollution problem especially in the oil rich areas where river sources and coastal 
waters are most polluted with petroleum wastes (Ibanga, 1978). Niger Delta remains 
the most impacted region by oil spillages and has resulted to, amidst others, frequent 
vandalization of oil installations. Recently, the issue of pipeline vandalization has 
caused a wide spread environmental alarm all over the country as the occurrences of 
vandalization is not restricted to the oil producing area alone. Incidents of Oil 
pipeline explosion Disaster in Nigeria between 1998 and 2008 is presented in tab 2.3. 
A number of petroleum contaminated sites requiring cleanup in Nigeria is on the 
increase, therefore more research into the use of inexpensive, easily accessible and 
environmentally friendly measures to reclaim these areas becomes necessary.                                                                            
   
 
30 
 
 
 
                                   Table 2.2        Oil spill data: SPDC 1995-2013 
 
 
   Number of spills Volume in barrels (bbl) 
1995 235 31,000 
1996 326 39,000 
1997 240 80,000 
1998 248 50,000 
1999 320 20,000 
2000 330 30,000 
2001 302 76,000 
2002 262 19,980 
2003 221 9,916 
2004 236 8,317 
2005 224 11,921 
2006 170 20,000 
2007 320 32,000 
2008 215 100,000 
2009 190 104,000 
2010 175 28,000 
2011 210 16,000 
2012 190 26,000 
2013 200 20,000 
Total 4614 722,134 
 
 
Source: SNAR, 2005; Shell spill incident data, 2013    
 
                                                                                                                                         
31 
 
 
                          
Table 2.3  Incidents of Oil pipeline explosion Disaster in Nigeria (1998-2008)  
 
DATE LOCATION/STATE DEATH TOLL OBSERVED 
CONSEQUENCES 
       May 16, 2008 Ijegun / Lagos Undetermined Many people were injured 
Dec. 2006 Ije-Ododo/ Lagos ≤ 1 Environmental pollution, 
damage to farmland 
May 30, 2005  Akinfo/Oyo ≤ 1 34 persons were injured, 15 
died after eleven days 
Sept 16, 2004 Ijegun/Lagos ≤ 60 Air and water pollution 
July 30, 2004 Agbani/ Enugu ≤ 7 Several people injured, 
environmental pollution 
June 19, 2003 Ovim in Abia state ≤ 125 Dozens of people injured, 
damage to farmlands 
November 5, 2001 Umudike, in Imo. ≤ 3 ≥17 people injured 
July 16, 2000 Oviri court / Delta ≤ 300  Dozens of people injured, 
environmental pollution 
July 10, 2000 Adeje, Delta state ≤ 150 Environmental pollution, 
damage to farmlands 
June 20, 2000 Okuedjeba, Delta State Undetermined Dozens of people injured, 
environmental pollution 
March 14, 2000 Umugbede , in Abia ≤ 50 Environmental pollution, 
state damage to farmlands 
February 7, 2000 Ogwe, Abia state ≤ 15 Environmental pollution, 
damage to farmlands 
June 8, 1999 Akute-Odo , Ogun ≤ 15 Damage to farmlands, 
pollution (air and water) 
October 18, 1998 Jesse, in Delta State ≤ 1000 Environmental pollution, 
damage to farmlands, dozens 
of people injured 
 
Source:  Adapted from Okoli et al., 2013  
32 
 
 
 
 
2.6   Remediation techniques for oil spills   
Remediation of petroleum polluted sites is not new and the methods used include; 
engineering, pump-and–treat, soil vapours extraction, sparging, chemical washes etc. 
Most of these remediation technologies have been used and are effective but they are 
known to be generally expensive and require professionals. However, bioremediation 
is a cheaper and a more environmentally friendly approach to resolving the problems 
of contaminated soils.  Bioremediation is one of nature's prudent ways to purify the 
polluted environment and that degraded by the anthropogenic activities. Although, 
the term “bioremediation” may be recent, the process is not a new one, (Hoff, (1993; 
Atlas, 1995a).  Its origin relates to the origin of life when the first organism was 
stressed by certain compounds and it evolved the process to convert such compounds 
into less harmful forms by adopting certain detoxifying mechanisms in order to 
overcome the stress.  
Bioremediation is a useful method for soil remediation, if pollutant 
concentrations are moderate and non-biological techniques are not economical.  
Microbiologists have studied the process since the 1940s. However, bioremediation 
became known to a broader public in the U.S. only in the late 1980s as a technology 
for cleanup of shorelines contaminated with spilled oil. The Exxon Valdez oil spill in 
1989 in Prince William Sound, Alaska was the catalyst for this attention. In the years 
since 1989, bioremediation has become a technology that is discussed, applied, and 
considered in many different circumstances (Hoff, 1993), the history of 
bioremediation in spill response can be divided into three development periods 
according to Hoff, 1993: the „courtship‟ period until 1989, the „honeymoon‟ period 
from 1989 until 1991, and the „establishment‟ period since 1992. 
 Biodegradation is a large component of oil weathering and is a natural process 
whereby bacteria or other microorganisms alter and break down organic molecules 
into other substances, eventually producing fatty acids and carbon dioxide (Hoff, 
1993). Bioremediation is the acceleration of biodegradation by adding exogenous 
microbial populations, stimulating indigenous populations or by manipulating 
33 
 
 
contaminated media using techniques like aeration and temperature control or 
addition of nutrients (Hoff, 1993; Atlas, 1995b; Swannell et al., 1996).  
 Many microorganisms possess the enzymatic capability to degrade petroleum 
hydrocarbons. Some microorganisms degrade alkanes, others aromatics, and others 
both paraffinic and aromatic hydrocarbons. Often the normal alkanes in the range C10 
to C26 are viewed as the most readily degraded, but low-molecular-weight aromatics, 
such as benzene, toluene and xylene, which are among the toxic compounds found in 
petroleum, are also very readily biodegraded by many marine microorganisms. More 
complex structures are more resistant to biodegradation, meaning that fewer 
microorganisms can degrade those structures and the rates of biodegradation are 
lower than biodegradation rates of the simpler hydrocarbon structures found in 
petroleum. The greater the complexity of the hydrocarbon structure, i.e., the higher 
the number of branched methyl substituent or condensed aromatic rings, the slower 
the rates of degradation (Atlas, 1995a). 
PAHs in contaminated soils can be treated with bioremediation. The oxidation 
of PAH involves oxygenases (monooxygenases and dioxygenases). Fungi complete 
the process by adding an oxygen to the substrate PAH to form arene oxides and then 
enzymatically adding water to form trans-dihydrodiols and phenols. Bacteria mainly 
use dioxygenases, adding two oxygens to the substrate and the further oxidizing it to 
dihydrodiols and dihydroxy products. Ring oxidation is the rate limiting step in the 
reaction, and subsequent reactions occur fairly quickly, yielding the typical 
metabolic intermediate Catechol found in Lignin degradation as well as Gentisic and 
Protocatechuic Acids (Philip et al., 2005). 
Intermediate metabolites degrade further through ortho and meta ring cleavage 
to produce succinic, fumaric, pyruvic, and acetic acids and acetyl-CoA, which are 
shunted into major metabolic and anabolic pathways. The byproducts of these 
reactions are carbon dioxide and water. The breakdown of PAHs can be 
accomplished by microorganisms that use PAH as their energy and carbon source, 
and also by other microbes through a process termed "co-metabolism." Co-
metabolism refers to the degradation of two compounds, one of these compounds the 
microbe obtains energy from, while the other is degraded "unintentionally." In such 
cases, the microbe directs it enzymes at the primary substrate, but these enzymes are 
34 
 
 
also capable of degrading the pollutant. Co-metabolism has been shown to be an 
important phenomenon in the bioremediation of larger aromatic chains (Philip and 
Atlas, 2005).  
The biodegradation of petroleum in the environment is carried out largely by 
diverse bacterial populations. The hydrocarbon-biodegrading populations of the 
marine environment for example are widely distributed in the world‟s oceans; 
surveys of marine bacteria indicate that hydrocarbon-degrading microorganisms are 
ubiquitously distributed in the marine environment (Prince and Atlas, 2005). 
Generally, in pristine environments, the hydrocarbon-degrading bacteria comprise < 
1% of the total bacterial population. These bacteria presumably utilize hydrocarbons 
that are naturally produced by plants, algae, and other living organisms. They also 
utilize other substrates, such as carbohydrates and proteins.     
When an environment is contaminated with petroleum, the numbers of 
hydrocarbon-degrading microorganisms are known to increase rapidly. Particularly, 
in marine environments contaminated with hydrocarbons, there is an increase in the 
proportion of bacterial populations with plasmids containing genes for hydrocarbon 
utilization. The proportions of hydrocarbon-degrading bacterial populations in 
hydrocarbon-contaminated marine environments often exceed 10% of the total 
bacterial population (Atlas, 1995a; Prince and Atlas, 2005) 
  2.7 Bioremediation techniques 
 There are several bioremediation techniques; the underlying idea is to 
accelerate the rates of natural hydrocarbon biodegradation by overcoming the rate-
limiting factors. Several techniques can lead to the results striven for. Indigenous 
populations of microbial bacteria can be stimulated through the addition of nutrients 
or other materials. Exogenous microbial populations can be introduced in the 
contaminated environment (bioaugmentation). If necessary, genetically altered 
bacteria can be used. Once the bacteria are chosen, the engineer must carefully meet 
their nutritional needs by choosing the correct mix of fertilizer (Irwin, 1997). 
Furthermore, the contaminated media can be manipulated by, for example, aeration 
35 
 
 
or temperature control. Two of these concepts involved include: seeding with 
microbial cultures and environmental modification.   
The success of microorganisms in biodegradation depends upon a wide array 
of variables and conditions, which often limit effective bioremediation and might 
include oxygen and nutrient availability, pH, C:N ratio, presence, number and 
activity of organic contaminant degrading microorganisms, enzyme induction, 
temperature, toxic levels of contaminants, presence of co-contaminants (determining 
added toxic effects or preferential degradation), and presence of terminal electron 
acceptors (Atlas, 1995b; Boopathy, 2000 and Romantschuck et al, 2000). 
Some bioremediation techniques include composting, bioaugmentation, 
phytoremediation and zooremediation. Composting was originally applicable for 
organic waste conversion into mulch and soil conditioner. It is now being applied to 
the hazardous waste treatment. Composting involves conversion of waste to less 
complex and relatively more stable material, significant decrease of water content 
and reduction of mass of the residue. Materials which are amenable to the 
bioremediation composting process include sewage sludge, soils contaminated with 
diesel fuel or other petro-products, wastes from brewing etc. Bulking agents like 
fibrous plant material, wood chips, bark, are added to increase porosity so as to 
improve aeration (Zachery and Reid, 2008a) 
Bioaugmentation is the enhancement of decontamination in the media or waste-
biodegradation by seeding of competent microflora and supplemented with desired 
level of nutrients. Faster decontamination has been achieved successfully by 
stimulation of existing microbial populations or augmentation with adapted strains. 
Thus, augmentation refers to establishing suitable conditions for bioremediation by 
means of adding nutrients for growth promotion, addition of terminal electron 
acceptor (oxygen or nitrate), moisture level adjustment or raising the temperature 
(Lloyd et al., 2005)  
Phytoremediation is a cost-effective, simple and sustainable beneficiary 
technique to remove pollutants from the environmental components - air, water or 
soil, using plants. It is a nondestructive and cost-effective technology employed to 
clean up contaminated soils. Phytoremdiation has been used on target contaminants 
36 
 
 
like metals, metalloids, petroleum hydrocarbons, pesticides, explosive or toxic gases, 
chlorinated solvents and a range of industrial by-products. Commercially viable 
phytoremediation systems for clean-up of shallow aquifers and water-borne 
contaminant are now well in practice. (Biobasic, 2006) 
Zooremediation involves the decontamination of environment through the 
activities of animals. Animals used for this purpose include the range of different 
arthropods, fishes, other filter feeders in aquatic systems and earthworms in solid 
organic waste management systems. It has been demonstrated that many aquatic 
animals were successfully used for water pollution treatment but it has not been 
encouraged owing to significant ecological safety reasons. However, earthworm 
based technology has proved commercial potentials as the role of earthworms in the 
conversion of organic materials and improvement of soil has been observed and 
appreciated (Biobasic, 2006; Zachery and Reid, 2008a) 
              2.8 Earthworms and their ecological importance 
Earthworms are either earthmovers or composters. Earthmovers tend to be 
solitary species which tunnel through the earth, aerating, decompacting and mixing 
soil strata and thus making surface nutrients available to plant roots at lower levels. 
Composters live en masse in organic matter on the soil surface, where they consume 
bacteria present in dead vegetation, animals and manure, turning it into humus. 
Common worm species with market value include Eisenia fetida, Lumbricus 
rubellus, Lumbricus hortensis, Lumbricus terristris, Eudrilus engeniae, Eisenia 
andrei, and Perionyx excavatus. Some of these species and other species share 
similar common names even while their sizes, appearances, natural habitats, feeding 
and breeding habits, temperature requirements and behaviors are quite different. 
(Kale and Karmegam, 2010).  
Earthworms are key organisms in (environmental) toxicology; Interest in 
earthworm ecotoxicology can be traced back to the inception, ring-testing and 
international standardisation of the acute earthworm toxicity test (OECD, 1984). 
Acute toxicity test was designed to be included in the risk assessment framework for 
newly registered chemicals and pesticides and the earthworm Eisenia fetida was 
37 
 
 
identified as a model organism for assessing the effects of chemicals on terrestrial 
saprotrophic invertebrates. 
On the other hand, earthworms are hardy organisms being capable of surviving 
highly toxic environment like being the only survival soil fauna after the 1976 
Seveso chemical plant explosion in Italy (Satchell, 1983)  
                2.8.1  Earthworm use for remediation and ecotoxicity 
Charles Darwin referred to earthworms as “unheralded soldiers of mankind”; 
this was one of the earliest references of the wonder works of earthworms. Their role 
as waste managers is well documented by vermiculture scientists but recently, 
research in the use of earthworms is tending towards its role in remediation of soil 
pollutants, development of medicine, as feeds in fisheries and dairy including its use 
as raw materials in rubber, lubricant, soap and detergent industries (Sinha, et al., 
2010). 
Earthworms can be employed in bioremediation strategies to promote 
biodegradation of organic contaminants. This is because of their biological, chemical 
and physical activities ranging from burrowing , production of casts both surface and 
below ground, its internal gut and processes, its surface in contact with the soil, other  
biological, chemical and physical interactions, in addition to the associated soil 
microorganisms (Brown and Doube, 2004).   Earthworms aerate and bioturbate soils 
and improve their nutritional status and fertility, which are variables known to limit 
bioremediation. Earthworms also retard the binding of organic contaminants to soils, 
release previously soil-bound contaminants for subsequent degradation, and promote 
and disperse organic contaminant degrading microorganisms (Zachery and Reid, 
2008a). 
In any bioremediation strategy, it is often necessary to ensure appropriate 
moisture, oxygen and nutrient levels, while ensuring that they can be homogenously 
dissipated, especially if, for example, dealing with deeper soils, compacted soils or 
soils rich in clay. Although techniques exist which is in use in the optimization of 
these variables, they could be time consuming, labour intensive and expensive 
methods. There might be a relatively low input, low technological tool available to 
38 
 
 
undertake this work. As earthworms move throughout the soil environment, their 
resulting burrows  act as input points of, and preferential pathways for, water and 
particle movement (Kretzshmar, 1984; Shipitalo and Le Bayon, 2004 and 
Dominguez, 2004), and nutrient flow and aeration (Dominguez, 1998; Zachery and 
Reid, 2008b).  
     Earthworms are useful in degradation of agrochemicals (Eijsackers et al, 
2001), petroleum and crude oil hydrocarbons, polycyclic aromatic hydrocarbons 
(PAHs), Polychlorinated biphenyls (PCBs) and other compounds by increasing 
hydrocarbon availability and remobilizing dichlorodiphenyltrichloroethane (DDT) 
and hexachlorocyclohexane (HCH) bound residues (Verma and Pillai, 1991), 
however, such findings were in conflict with those of (Bolan and Baskaran, 1996) 
who investigated the effect of earthworm (Lumbricus rubellus and Allolobophora 
14 14
calignosa) casts upon the sorption and movement of C-atrazine, C-2,4-
14
dichlorophenoxy acetic acid (2,4-D) and C-metsulforon methyl. They stated that 
the casts absorbed higher amounts of herbicides than the source soil due to the higher 
levels of organic carbon and fine size fractions, present due to earthworm grinding 
actions and selective feeding. Although both theories are plausible, they emphasize 
both the differences in compound behaviour, experimental set-up or earthworm 
species and the wide variability between the effects of earthworm mechanics upon 
compound fate and subsequent earthworm casts upon compound fate (Philip and 
Atlas, 2005; Zachery and Reid, 2008). 
Ecotoxicity test with earthworm can be used for artificial soil acute toxicity test, 
in screening chemical toxicity. These include not only classical toxicity studies but 
also field soil assessment, remediation evaluation and evaluations of bioavailability 
(Spurgeon et al. 2004; Edwards and Bohlen 1996). Several factors are of importance 
when using earthworm for ecotoxicity test; Weight loss during acute tests is a 
validation criterion to be considered. If more than 15-20% weight loss occurred in 
the control, it would indicate the test was not valid because the earthworms were 
unhealthy or the substrate not suitable for the test. Observation of significantly more 
weight loss than this in treatments should be considered as an indication of sublethal 
effects (OECD, 1984). For studies specifically measuring weight loss, it is 
39 
 
 
recommended to ensure an even weight distribution at the outset between treatments. 
It is also important to measure chemical availability during toxicity tests. This 
included not only total chemical in the soil, but also potentially bioavailable and 
body residue levels (Spurgeon et al. 2004).  
Studies using earthworms in ecotoxicity of petroleum pollution are reported; 
most indicates its use as toxicity assays in monitoring bioremediation of petroleum 
sites (Knoke, et al, 1999; Lors et al, 2009). Knoke et al, (1999) used five bioassays 
to measure toxicity during bioremediation of a soil contaminated with 
pentachlorophenol (PCP; 335 ppm), polycyclic aromatic hydrocarbons (PAHs; 1225 
ppm) and petroleum hydrocarbons (19125 ppm). Different bioremediation treatments 
were tested in soil microcosms including amendment with phosphorus and/or PCP-
degrading Pseudomonas sp. UG30, either as free cells or encapsulated in κ-
carrageenan. Soil toxicity was monitored using the solid-phase Microtox test, SOS-
chromotest, lettuce seed germination, earthworm survival and sheep red blood cell 
(RBC); the trend indicated earthworm survival LC50 values varying with each 
treatment with results showing toxicity trends in a contaminated soil during 
bioremediation differ according to the assay used. 
A determination of the limits and extent of hydrocarbon biodegradation using 
earthworm and plant toxicity and waste leachability of crude oil-containing soils was 
carried out by Salanitro, et al., 1997. Three oils (heavy, medium, and light of API 
gravity 14, 30, and 55, respectively) were mixed into silty loamy soils containing 
low (0.3%) or high (4.7%) organic carbon at 4000−27 000 mg/kg TPH. Most oily 
soils were initially toxic to earthworms in which few animals survived in 14-day 
bioassays. In a solid phase Microtox test, most oily soils had EC50 values that were 
≤50%. Seed germination and plant growth (21-day test, wheat and oat but not corn) 
were also significantly reduced (0−25% of controls) in untreated soils containing the 
medium and light crude oils but not the heavy oil. Bioremediated soils were neither 
toxic to earthworms, inhibitory in the Microtox assay, nor inhibited seed germination 
after 5 (high organic soil) or 10−12 (low organic soil) months of treatment. Data 
suggested that the remaining petroleum compounds may be bound or unavailable in 
that they are not (a) biodegraded further, (b) toxic to soil-dwelling species 
(earthworms and plants), and (c) susceptible to leaching and subsequent impact to 
40 
 
 
groundwater. These findings provide a basis for a framework in which petroleum 
hydrocarbon-containing soils can be evaluated by ecological assessment methods 
such as biodegradability, ecotoxicity and leaching potential of regulated substances. 
 Lors et al, 2009 studied the performance of a biological treatment of a PAH-
contaminated soil with respect to its physicochemical and ecotoxicological 
properties. After six months, the biological treatment led to a significant reduction of 
2- and 3-ring PAHs and to a lesser extent to 4-ring PAHs. As a consequence a 
significant decrease of the acute ecotoxicity was observed passing from highly 
ecotoxic before treatment to non-ecotoxic according to Lactuca sativa seedling and 
growth inhibition test and Eisenia fetida mortality test. This could be related to the 
bioavailability of PAHs. Indeed, tests performed on aqueous leachates of the soil 
showed a strong decrease of 2- and 3-ring PAHs correlated with a significant 
reduction of acute and chronic ecotoxicity responses. The biological treatment led to 
the mutagenicity reduction and the genotoxicity disappearance in the leachate. Thus, 
bioassays are complementary to chemical analyses to evaluate the efficiency of a 
bioremediation process and to evaluate the bioavailability of the organic pollutants as 
the total concentration of a contaminant is not the only criterion to consider. The 
comparison of the ecotoxic responses allowed us to underline the best sensitivity of 
the earthworm, Microtox, Alga and Ames bioassays among the tested set. These 
bioassays could thus be good candidates to build a toxicity evaluation procedure for 
PAHs contaminated/ remediated soils.  
 Generally, earthworms bioaccumulate and biodegrade several organic and 
inorganic chemicals like tetra chorodibenzo-p-dioxin released during the Seveso 
explosion as recorded by Satchell, 1983, PAHs (Ireland, 1983; Contreras-Ramos et 
al, 2006), Endocrine distrupting chemicals (EDCs) from sewage e.g. bisphenol –A 
(Markman et al, 2007). They are also known to tolerate 1.5% crude oil (Hanna and 
Weaver, 2002).  
    2.8.2 Earthworms and heavy metals  
Earthworms were found to have high potential for the accumulation of some 
heavy metals like cadmium, mercury, lead, manganese, calcium, iron and zinc in 
polluted soils, (Hendriks et al., 1995) but are also known to disappear at low levels of 
41 
 
 
soil Cu and Ni (Klok et al., 2000). Lumbricus terristis, L. rubellus and D. rubida are 
known to accumulate high levels of lead and cadmium in their tissues (Ireland, 1983). 
Cadmium levels up to 100mg/kg was found in tissues of earthworms; L. terrestis 
could bioaccumulate 90-180mg/g of lead while L. rubellus and D. rubida assorbed 
2600mg/g and 7600mg/g of lead. Zinc, Manganese and iron are reported to be 
excreted through the calciferous gland of earthworms (Ireland, 1983 and Hartenstein 
et al., 1980). L .rubellus degraded soil spiked with PAHs (100µg/kg of phananthrene 
and fluoranthrene) after 56 days (Contreras-Ramos et al, 2006) recording 86% 
removal of phenanthrene 100% (Ma et al., 1995). E.fetida had reduced oil contents 
when compared with control. Earthworms can mineralize asphaltens and 
decontaminate hydrocarbon polluted soils (Ceccanti et al., 2006; Martin-Gil et al., 
2007 and Tomoko et al., 2005). Sinha, 2010 had shown that sludge (brittle and black) 
was transformed to homogenous and porous and light texture and over 80% free of 
cadmium and lead after a twelve weeks experiment.  
However, earthworms are considered useful for assessing heavy metal pollution 
in soils (Menzie et al., 1983). Though some metals like copper (Cu), iron (Fe), 
manganese (Mn), nickel (Ni) and zinc (Zn) are essential as micronutrients for life 
processes in plants and microorganisms, others like Cd, Cr and Pb are with unknown 
physiological activity, but are detrimental beyond certain limits (Bruins et al., 2000). 
       2.8.3 Action of earthworms in remediation  
Earthworms passively absorbs dissolved fraction through its body wall and 
ingest soil through its mouth followed by intestinal uptake during which they either 
biotransform or biodegrade contaminants. Some metals bind to metallothioniens (a 
protein found in earthworms), their chloragogen cells are suspected to accumulate 
heavy metals by their guts and then immobilize them in their small spheroidal 
chloragosomes and debris vesicles which the cell contains. Other substances 
degraded by earthworms in this manner include phthalate and flouranthene in soils. 
Generally, vermiremediation would cost $500 - $1000 per hectare while mechanical 
evacuation is estimated to cost $10, 000 – 15, 000 (Sinha, et al., 2010). Although 
there are several work indicating the use of earthworms for ecotoxicity or 
remediation, reports on the use of African earthworm species for remediation is 
42 
 
 
however limited and not readily available. However, Eudrilus eugeniae an 
earthworm species found in Nigeria, was not significantly effective in the 
remediation of spent engine oil (Ameh, et al., 2012) but caused a drop in total 
petroleum hydrocarbon content in soils from mechanic workshop after a 35 days 
exposure (Ameh, et al., 2013). On the other hand, there was reduction in population 
of Eudrilus eugeniae in petroleum polluted soils and dump site (Oboh et al., 2007).  
               2.9     Physicochemical parameters  
Several physiochemical analyses are important to be carried out when 
+
investigating portability of water samples; some of such include; hydrogen ion (H ) 
concentration (pH), total dissolved solutes (TDS), conductivity, total hardness, 
sulphate, calcium hardness, nitrate, phosphate, heavy metals including cadmium, 
copper, zinc, lead, nickel, vanadium and manganese and organic parameters; Total 
Petroleum Hydrocarbon (TPH), Total organic carbon (TOC) and Total organic matter 
(TOM). Petroleum spills have negative impact on the environment and in Nigeria such 
events are common placed in the Niger-Delta hence more reports of investigations on 
oil spills are focused on this area. 
Benka-Coker and Ekundayo, 1995 had reported the average total hydrocarbon in 
Ekeremor soil after an oil spill to range between 0.8 to 12.4 ppm while studies by Okop 
and Ekpo, 2012 on Ikot-Abassi soil reported 9 – 289 mg/kg. An assessment of soils 
from oil spill site in Mese, Ondo state showed that the average pH, moisture content 
and organic carbon were 6.7, 78.65 % and 2.76 % respectively compared with soils 
from a site in Bonny, River state having average pH, moisture content and organic 
carbon to be 4.6, 61.51% and 4.23% respectively. (Folake, 2013). Nickel and vanadium 
assessment of oil polluted soil from Ogbodo-Isiokpo (Rivers state) had shown Ni levels 
ranging from 0.15 to 1.65 mg/kg and V levels ranging from 0.19 to 0.70 mg/kg (Osuji 
and Adesanya, 2005). TPH levels recorded for both surface and groundwater within the 
vicinity of NNPC oil depot in Apata, Ibadan ranged from 20.34±1.79 to 27.40 ±5.32 
and 2.67±0.80 to 13.03±2.21mg/l respectively. Heavy metals like Pb, Cd, Zn, Ni, Cu 
and Cr in surface water and groundwater were reportedly higher than the WHO 
permissible limit and drinking water limits (Adewuyi amd Olowu, 2012). 
 
 
43 
 
 
                                                   CHAPTER THREE 
  3.0                                 MATERIALS AND METHODS 
  3.1 Study area 
This study was carried out in Agaye settlement in Ije –ododo community which 
o
is located in Iba (LSDC) Ojo local government area of Lagos State (Lat. 06  29'N 
o
and Long. 03  15' E) (Fig. 3.1). Lagos is a coastal city bounded by the Atlantic 
Ocean in the south. FAO, 2009, described Lagos to be ecologically located partly in 
the swampy mangrove and partly in the delta swamp area and climatically under the 
Equatorial Climate which extends from the coast to about 150km inland. Rainfall is 
between 1500 and 3000mm per annum, with an average temperature range of 17–
24°C and relative humidity ranging between 60–90%. It has two seasons, the wet 
season March to October, and dry season November to March having bi–modal 
rainfall maxima annually. Lagos majorly has the mangrove forest and coastal 
vegetation interspersed with numerous creeks and lagoons. The mangrove swamp is 
noted for the mangrove species of trees; Rhizophora, dominated by Rhizophora 
racemosa spp (occupying an estimated 99% of the entire mangrove area) and less 
frequently Conocarpus erectus and Laguncularia racemosa (white mangrove) 
(Garnier 1967; Iloeje 1980).  
Agaye falls under the swampy mangrove area lying north of the Lagos Badagry 
expressway and west of Festac town. The major surface water body is a wetland 
which suffices for a river with flowing water current towards the South during rainy 
season and dries up during dry season becoming a typical wetland with sparsely 
distributed patches of land. The surface water lies southwards of the settlement 
extending to the Lagos – Badagry expressway and Festac town, the water body 
remains inaccessible major parts of the year.  The only accessibility used to be 
through a constructed footbridge usually used by fishermen to access the inland of 
the water body; however, the footbridge is presently dilapidated. The other portion of 
Agaye settlement is land of flat topography with swampy terrain; the settlement was 
sparsely occupied by residential building at the time of the study. The remaining land 
was either bare or used for subsistence farming of staple crops like maize and 
cassava. The predominant farming practice involved the use of organic manure  
44 
 
 
a
b                                                                                                                                                          
 
c                                                                                                                                                          
 
                                                                                                                                                           
      Fig. 3.1 Map of Lagos state (a), indicating Ije-Ododo (b) and highlighting sampling points (c) 
45 
 
 
 
 
(chicken droppings) and crop rotation system. High pressure oil pipelines owned and 
monitored by the Nigeria National Petroleum Corporation (NNPC) are commonly found 
within the area and extending towards the inaccessible parts of the wetland. The study site 
was chosen because of the repeated oil spills in the area and its attendant health 
th
effect as reported in the Punch, a Nigerian newspaper of 29  Dec, 2006 (Plates 3.1 - 
3. 4) (Okoli et al., 2013). The petroleum product suspected to be spilled was 
Premium Motor Spirit (PMS). Subsequent oil spill had been reported to have 
occurred in Agaye by 2012 and 2013. There is no baseline record of physicochemical 
parameters of soil and water in this area. The contamination in this case was the 
accidental discharge of petroleum oil resulting from leaking oil pipelines lying 
towards the inaccessible wetland. This lasted for some weeks (eye witness account) 
and resulted in an inferno (engulfing a great portion of the wetland and 30 – 100m of 
land) that burned for days and could only be put out by the intervention of 
sophisticated fire fighting approach (use of helicopters).  
For this study, the area was delineated based on impact of the spill and inferno; 
sampling points were located 100m within the spill while the control was chosen 
from an area 500m away from the spill, this was to ensure soil type similarities 
because of the earthworm population study. There was an oil spill and fire outbreak 
that occurred in May, 2008 at Ijegun (an adjacent community located south of 
Agaye) about 1km away from the study site during the period of the study.  
 
 
 
 
 
 
 
 
 
 
46 
 
 
                           
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Plate 3.1 Resultant inferno in Agaye settlement, Iba LSDC, Ojo LGA, Lagos state 
th
after Oil Spill (Source: Punch Newspaper, 26  December, 2006) 
 
*Picture showing onlookers behind the community secondary school premises as they watch the   
fire out break ensued in Agaye settlement after the oil spill 
 
 
 
 
 
 
 
 
 
 
 
 
 
47 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Plate 3.2 Water body in Agaye after oil spill and inferno  
                             (Source: Field Survey, 2007) 
 
* Wetland covered with widespread oil films two months after the oil spill, an indication of the 
impact on the water body. 
 
 
 
 
 
 
 
 
 
 
48 
 
 
 
 
 
                       Plate 3.3 Agaye vegetation after oil spill and inferno                                                                                                        
                                        (Source: Field Survey, 2007) 
*The Raparian tree community out rightly destroyed by the inferno indicating the impact on the 
vegetation of Agaye community. 
  
 
 
 
 
 
49 
 
 
                                    
 
                      Plate 3.4 A farmland after oil spill and inferno  
                                 (Source: Field Survey, 2007) 
* A farmland within the area of inferno indicating the negative economic impact of 
the incident 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
50 
 
 
 
 
3.2  Sample collection and analysis - Quality assurance and quality control 
All containers (plastic and glass ware) were soaked in 1M HNO3 overnight 
(Onianwa, 2001) and washed with teepol, a laboratory detergent rinsed with tap water 
and finally with deionised water. Samples for organic analysis were collected using 
glassware while that for trace metals and other parameters were collected in plastic 
containers. Parameters such as temperature and pH were determined on the field. 
Wavelengths setting of the spectrometers used were done daily by the standard 
instrumental procedure and other equipments used were always calibrated against 
reference standards. Blank analyses were also carried out. 
               3.2.1  Water and Soil sampling  
 
Water samples, surface water (SW1 and SW2), groundwater including well water 
and borehole (GW1 – GW5) were collected once every two months. Surface water 
were collected 0 and 20m into the water body (from land) while ground water were 
collected from randomly selected sampling points 20, 40, 60, 80 and 100m away from 
water body, along transect of the spill. Well water was also collected 500m away from 
the sampling pont (GW6) served as control (Fig. 3.5). Sampling was done for 2 years 
between June, 2007 and April, 2009. Triplicate water samples were collected in glass 
bottles for hydrocarbon analysis while other water samples were collected in 5L 
plastic kegs for heavy metals and other physicochemical analysis carried out. Samples 
collected were then labeled as designated in Table 3.1. Triplicate soil samples were 
collected 0 - 20cm deep from eight locations around same loci of the groundwater 
sites (S1-S5; S6 as control) and Sv1 and Sv2 (sampled close to Sv1 and Sv2) using 
soil auger and packed into small polythene bags and labelled according to the 
locations (Table 3.2). These were taken to the laboratory for further treatment. 
 
 
 
51 
 
 
 
 
               Table 3.1  Sampling points, designation, description and GPS locations   
 
Sample designation  Description  GPS Location  
   
o
GW1 / S1 Well 1  N 06  29. 40'  
o
 E003  15. 23'  
o
GW2 /S2 Well 2 N 06  29. 41'  
o
  E003  15.20'  
o
GW3 /S3 Well 3  N 06  29.42'  
o
E003  15. 24' 
o
GW4 /S4 School Well E003  15.19' 
o
  N 06  29. 44'  
o
GW5/S5 School Borehole water N 06  29. 43'  
o
 E003  15. 25' 
o
GW6//S6 Control well       N 06  30. 00'  
o
  E003  15.25' 
o
SW1/SV1 Wet land 1 N 06  29. 092'  
o
 E003  15. 297'  
o
SW2/SV2 Wet land 2 N 06  29. 110'  
o
  E003  15. 302'  
 
 
 
 
 
 
 
52 
 
 
 
 
   3.3 Physicochemical analyses 
                3.3.1    Water analysis 
Collected water samples were analyzed and parameters such as pH, conductivity, and 
temperature were determined in-situ. All other samples were packed in ice inside a cooler and 
transported to the laboratory within six hours of collection for further analysis or preservation. 
2ml of Hcl was added to 1L of samples for heavy metal analysis and kept in the refrigerator at 
O
4 C until the time of analysis. 
                3.3.1.1  Heavy metals 
 
Heavy metals were determined by digesting a known volume of water sample 
with analytical grade HNO3. The digested sample was filtered into a 50 ml standard 
flask, made up to the mark with deionized water and stored in a nitric acid pre-washed 
polyethylene bottle in the refrigerator prior to chemical analysis. The water extracts 
were analyzed for metals (Pb, Mn, Zn, Ni, Cd, Cr, V and Cu) by atomic absorption 
spectrometer (Schimazo model 2380). Triplicate samples were analyzed and the mean 
values recorded (APHA, 1998). 
                3.3.1.2  pH 
 
 The pH of water samples was determined by a pH meter (Hand held Hawna pH 
meter, Hi-8424). The pH meter was calibrated using a three point calibration method. The 
water sample was stirred vigorously using a clean glass stirring rod and 50 ml of the 
sample was poured into the glass beaker using the watch glass as a cover. The sample 
was allowed to stand to allow for temperature stabilization. Stirring was occasionally 
done while waiting. The pH meter was standardized by means of standard solutions with 
known pH. The pH meter electrode was immersed into each water sample and allowed to 
stabilize in the sample before reading was made. After each reading the electrode was 
rinsed well with distilled water, and then dabbed lightly with tissues to remove any film 
formed on the electrode.  
 
 
53 
 
 
 
 
                3.3.1.3  Temperature 
 
Temperature was measured using portable calibrated mercury in glass 
thermometer (EPA, 1998) at the collection point. Temperature measurement was made 
by taking a portion of the water sample (about 1litre) and immersing the thermometer 
into it for a sufficient period of time (till the reading stabilized). 
                3.3.1.4           Total Dissolved Solid (TDS) 
 
The difference in the weights of Total Solids (W1) and Total Suspended Solids 
(W2) expressed in the same units gives Total Dissolved Solids (TDS). Fifty millimeter 
(50ml) of a well-mixed sample was measured into a pre-weighed dish and evaporated 
o 
to dryness at 103 C on a steam bath. The evaporated sample was dried in an oven for 
o 
about an hour at 103-105 C and cooled in a desiccator and recorded for constant 
weight (W1). Another vigorously shaken 50ml of the sample was filtered into a pre-
weighed glass fibre filter disk fitted to suction pump, and washed successively with 
distilled water. The filter was carefully removed from the filtration apparatus and dried 
o 
for an hour at 103-105 C in an oven, cooled in dessicator and weighed for constant 
weight (W2). 
Total Dissolved Solids (mg/L) =   (W1-W2) (1000) / Sample volume (ml)  
(APHA, 1992) 
                3.3.1.5          Total Hardness (TH)  
 
50ml of a well-mixed sample was put into a conical flask using a pipette, to 
which 1ml of ammonia /ammonium chloride buffer of pH 10 and 2-3 drops of 
Eriochrome black -T indicator were added. The mixture was titrated against standard 
0.01M EDTA until the wine red colour of the solution turned pale blue as the end 
point (APHA / AWWA/ WEF, 1995). 
               Total hardness (mg/L) = (T) (1000) / V 
               Where, T = Volume of titrant 
                V = Volume of sample 
54 
 
 
 
               3.3.1.6  Conductivity 
 
Conductivity was measured with a conductivity meter (Accumet Basic AB30) 
calibrated with potassium chloride solution. The electrode of the conductivity meter 
was dipped into the sample, and the readings were noted at stable value. 
-
               3.3.1.7 Chloride (Cl ) and Alkalinity  
 
-
Chloride (Cl ) was determined by Mohr‟s titration mothod. 20 ml of sample was 
placed in a conical flask and pH adjusted to 6 - 8 with small amount of (0.1 M) 
calcium carbonate solution. One millilitre of potassium chromate solution prepared by 
dissolving 50 g of potassium chromate in 1L of distilled water was added and the 
solution was titrated with (0.0141 M) silver nitrate solution with constant stirring. 
Alkalinity (Aci-Base titration) was determined by titrating known volumes of 
water sample with 0.10M HCl. One hundred milliliters (100ml) of water sample was 
poured into a 250ml Erlenmeyer flask followed by addition 3-5 drops of methyl 
orange. The burette to be used was rinsed twice with the acid solution for titration 
(0.1M HCl); this was only done before the first titration. The burette was then filled 
with the acid and the initial volume recorded. The sample was titrated with the 0.1M 
HCl to the endpoint (orange to red), and the final volume recorded. The alkalinity of 
the sample in ppm (mg/l) was calculated by using the equation below: 
 Alkalinity = [(ml of HCl) (Molarity of HCl) (100.0g/mol)] / [(2) (ml of sample)]  
                3.3.1.8     Sulphates  
 
One hundred millimeters (100ml) of the sample was filtered into a Nessler's tube 
containing 5ml of conditioning reagent. About 0.2g of barium chloride crystals was 
added with continued stirring. A working standard was prepared by taking 1ml of the 
standard H2SO4, 5ml of conditioning reagent and made up to 100ml, to give 100 NTU. 
The turbidity developed by the sample and the standards were measured using a UV 
Spectophotometer. 
55 
 
 
                 
                3.3.1.9     Phosphate  
 
To 50ml of the filtered sample, 4ml of ammonium molybdate reagent and about 
4-5 drops of stannous chloride reagent was added. After about 10 min to 12 min, the 
colour that developed was measured using UV spectrophotometer at 690nm and 
calibration curve was prepared. A blank sample was also prepared. The value of 
phosphate was obtained by comparing absorbance of sample with the standard curve 
and expressed as mg/L (APHA 1992, APHA/AWWA, WEF, 1995) 
                3.3.1.10       Nitrate  
 
Nitrate was determined by uv-spectrophotometric method. 50ml of the sample 
was pipetted into a porcelain dish and evaporated to dryness on a hot water bath. 2ml 
of phenol disulphonic acid was added to dissolve the residue by constant stirring with 
a glass rod. Concentrated solution of sodium hydroxide and distilled water was added 
with constant stirring to make it alkaline. This was filtered into a Nessler's tube and 
made up to 50ml with distilled water. The absorbance was read at 410nm using a 
spectrophotometer after the development of colour. The value of nitrate was found by 
comparing absorbance of sample with the standard curve and expressed in mg/L. 
(APHA/AWWA, WEF, 1995) 
                3.3.1.11     Total petroleum hydrocarbon  
 
  Oil and grease was first determined by partition – gravimetrc method. Sample 
levels were marked on sample bottle at the water meniscus (to later determine sample 
volume). Sample was acidified with 1:1 HCl to pH 2 by adding 5 mL in 1 L sample. 
Sample was transferred to a separatory funnel and sample bottle was carefully rinsed with 
30 mL 100% n-hexane and solvent washings were added to separatory funnel. The 
mixture was shaken vigorously for 2 min and layers were left separate. Aqueous layer 
was drained with small amount of organic layer into original sample container. Solvent 
layer was drained through a funnel containing a filter paper and 10 g Na2SO4, both of 
which have been solvent-rinsed, into a clean, distilling flask. Solvent layer with estimated 
>5mg emulsion, including draining emulsion and solvent layers were drained into a glass 
56 
 
 
centrifuge tube and centrifuge for 5 min at approximately 2400 rpm. Centrifuged material 
was then transferred to an appropriate separatory funnel and solvent layer was drained 
through a funnel with a filter paper and 10 g Na2SO4, both of which have been prerinsed, 
into a clean, distilling flask. 
Aqueous layers were recombined with any remaining emulsion or solids in 
separatory funnel. With clear solvent, centrifuging process is not necessary. Extraction 
was done twice more with 30 mL solvent each time, but sample containers were first 
rinsed with each solvent portion. Centrifugation step was repeated if emulsion persisted 
in subsequent extraction steps. Extracts were combined in distilling flask, and a final 
rinsing of filter and Na2SO4 with an additional 10 to 20 mL solvent were included in 
flask. Solvent was then distilled in distillation flask with a distillation adapter equipped 
with a drip tip in a water bath at 85°C and solvent was collected in an ice-bath-cooled 
receiver. When visible solvent condensation stopped, flask was removed from water 
bath. Flasks were dried on cover water bath still on at 85°C, for 15 min. Air was drawn 
through flask using a suction pump for the final 1 min. Distillate was cooled in 
desiccator for at least 30 min and weighed. 
Oil/grease in mg/L was calculated by: A-B X 1000 
         mL Sample 
TPH was then determined by redissolving the extracted oil and grease in 100 mL 
n-hexane. To 100 mL solvent, 3.0 g silica gel/100 mg total oil and grease was added, up 
to a total of 30.0 g silica gel (1000 mg total oil and grease). Container was stoppered and 
stirred on a magnetic stirrer for 5 min and solution was filtered through filter paper pre-
moistened with solvent, silica gel and filter paper were washed with 10 mL solvent and 
combined with filtrate. Solvent was then distilled in distillation flask with a distillation 
adapter equipped with a drip tip in a water bath at 85°C and solvent was collected in an 
ice-bath-cooled receiver. When visible solvent condensation stopped, flask was removed 
from water bath. Flasks were dried on cover water bath still on at 85°C, for 15 min. Air 
was drawn through flask using a suction pump for the final 1 min. Distillate was cooled 
in desiccator for at least 30 min and weighed. 
 
TPH in mg/L was calculated by: A-B X 1000 
           mL Sample 
57 
 
 
              Where A =Total gain in weight of distilling flask and  
                          
                          B = less calculated residue from solvent blank 
 
                3.3.2  Soil analysis 
               Soil samples (0-20cm deep) were collected in triplicates from eight locations around 
same loci of groundwater sites using soil auger. Samples were prepared based on the 
analysis to be done and the methods are described below; 
                3.3.2.1    Heavy Metal Analysis 
 
The soil samples were air–dried, crushed and passed through a 2mm sieve. A 
portion (1g) of the soil sample was digested in a 2 M nitric acid. The heavy metals 
determined in the analysis were Cr, Cd, Pd, Zn, Cu, Mn, Ni and V. The concentrations 
of the metals in the digested soil sample solutions were determined with atomic 
absorption spectrometer (Schimazo model 2380) within three weeks. Each sample was 
analyzed in triplicate and the average of the results reported. Actual concentration was 
calculated with the formular below: 
                                                             Weight of sample in mg 
                    AAS reading    =                                                                                                                                 
                                                         Volume in liters 
              
                3.3.2.2  pH 
 
pH measurement was performed using Accumet pH Model 15 meter (Fisher 
Scientific). The pH meter was calibrated with standard buffer solutions of pH-4, pH-  
7 and pH-10. Between sample analyses, the electrode was rinsed with distilled water 
and gently blot-dried with tissue. Constant stirring of sample was performed to quickly 
reach a steady potential. Soil pH was measured using EPA Standard method No. 
9045C (USEPA, 1987). It involved adding 20±0.1g of soil to 20 ml of distilled water 
and continuously stirring for 5 minutes. After allowing the soil suspension to stand for 
about 1 hour, most of the suspended clay was allowed to settle out from the 
suspension then pH measurement was taken on the aqueous phase. The glass electrode 
was immersed just deep enough into the clear supernatant solution to establish good 
o
electrical contact. All results are reported as “soil pH measured in water at 25 C, 
58 
 
 
which is the temperature at which pH meter is calibrated. Three replicates per sample 
were done. 
                3.3.2.3     Conductivity 
 
A 1:5, soil to water suspension ratio was prepared by weighing 10 g air-dried soil 
(<2 mm) into a bottle. 50 ml deionised water was added and the resulting solution 
mechanically shake at 15 rpm for 1 h to dissolve soluble salts. The conductivity meter 
was calibrated using the KCl reference solution to obtain the cell constant. 
Before usage the cell was rinsed thoroughly with deionised water before the 
measurement of the electrical conductivity of the 0.01M KCl at the same temperature 
as the soil suspensions was done. The conductivity cell was then rinsed with the soil 
suspension before refilling the conductivity cell without disturbing the settled soil. The 
value indicated on the conductivity meter was recorded.  The cell was rinsed with 
deionised water in-between sample analysis (Rayment and Higginson, 1992). 
                3.3.2.4    Sulphates  
 
Ten grams (10 g) air-dried, sieved soil was placed into a 50 ml Erlenmeyer flask. 
A twenty five millimeters (25 ml) of monocalcium phosphate extracting solution was 
added and solution shaken at 200 rpm for 30 minutes. 0.25 g of charcoal was then 
added and shaken for an additional 3 minutes. The resulting solution was filtered 
through sulphate-free filter paper (Whatman No. 42) (Schulte and Elk, 1988).  Ten 
millimeters (10 ml) of the filtrate was pipetted into a 50 ml Erlenmeyer flask, and 1 ml 
of acid "seed" solution added. The Erlenmeyer flask and solution were gently swirled 
before adding 0.5 g of BaCl2.2H2O crystals. 
The mixture was left to stand for one minute, and then placed on magnetic stirrer 
until the crystals were dissolved. A UV spectrophotometer was used to read the 
transmittance at a wavelength of 420 nm for samples and standard solutions. A plot of 
percent transmittance reading vs. concentration for standard curve was obtained from 
which sample concentration was determined (APHA, 1985). 
4- 
mg SO S/kg of soil   =   mg S /L x 0.025L / 0.010 kg soil   =   mg S/L x 2.5 
Where S = Sample 
59 
 
 
                3.3.2.5    Phosphate  
 
Nearly all methods of determining Phosphate in soil involve extraction into a 
liquid phase. Deionized water is a commonly used extractant for Phosphate analysis 
(Potter, 1992). Soil samples were extracted by a deionized water extraction method 
with a soil: extractant ratio of 1:10. Samples were shaken in 50 ml conical tubes for 60 
minutes at 180rpm on an orbital shaker. The tubes were centrifuged for 10 minutes at 
2500rpm. After centrifugation, extracts were decanted and filtered. Filtered extracts 
were stored at room temperature for analysis.  
Soil samples were analyzed by ascorbic acid colorimetry (Murphy and Riley 
1962). To prepared samples, 4.0 ml Reagent B and 19.0 ml deionized water was added 
to 2.0 ml of each extract. Standards consisting of 5.0 ml of each standard Phosphate 
solution (0.1 ppm to 1.0 ppm P), 4.0 ml Reagent B, and 16.0 ml deionized water and a 
0.0 ppm P standard consisting of 4.0 ml Reagent B and 21.0 ml deionized water were 
also prepared. Samples were allowed 30 minutes for colour development. The 
absorbance of the samples and standard solutions at 882 nm was measured with a 
Perkin Elmer Lambda 25 UV/VIS spectrophotometer.  
Reagent A: Mixture of 6g Ammonium molybdate, 0.146g Antimony potassium 
tartrate and 72ml Sulphuric acid all brought to 1 litre with deionized water. 
Reagent B: Mixture of 1.584g/ l ascorbic acid and 300ml reagent A  
    3.3.2.6    Nitrate  
 
Five grams (5 g) of air-dried, ground and sieved (2 mm) soil was placed into a 
125 ml Erlenmeyer flask. 50 ml of 0.01 M CaSO4 was then added. The solution was 
shaken for 15 minutes on a reciprocating shaker at 200 rpm. The resulting soil 
suspension was then filtered using Whatman No. 2 filter paper to provide a clear 
-
filtrate without contributing measurable amounts of NO3 –N to the filtrate. The extract 
was then measured colorimetrically using Cd reduction method (Keeney and Nelson, 
1982).  
 3.3.2.7  Potassium  
The filter of the flame photometer was set at 766.5 nm (marked for Potassium, K) 
and the flame was adjusted for blue colour. The scale was set to zero and maximum 
60 
 
 
using the highest standard value. A standard curve of different concentration was 
prepared by feeding the standard solutions. The sample was filtered using filter paper 
and filterate was fed into the flame photometer. The concentration was found as direct 
reading (Hussain et al., 2000). 
 
                3.3.2.8  Sodium  
 
The filter of the flame photometer was set to 589nm (marked for Sodium, Na). By 
feeding distilled water the scale is set to zero and maximum using the standard of 
highest value. A standard curve between concentration and emission was prepared by 
feeding the standard solutions. The sample was filtered through filter paper and fed 
into the flame photometer and the concentration was found by direct readings 
(Hussain et al., 2000). 
                3.3.2.9          Calcium  
 
5ml aliquot of soil extract was pipetted into 50ml white porcelain dish and diluted 
with distilled water to a volume of approximately 25ml. 2ml of 4 M NaOH and 2-3 mg 
of cal red indicator was then added. The resulting solution was titrated slowly with 
0.01 M EDTA until a sky-blue end point was obtained. A blank titration was also done 
using 5ml distilled water. 
1000 X (Vol. EDTA used for soil extract – Vol. EDTA for blank) X N of EDTA soln. 
___________________________________________________________ 
                                                 Vol. sample taken (aliquot) 
               3.3.2.10 Total Organic Carbon and Total Organic Matter (TOC and TOM) 
One gram (1g) of soil samples were crushed to pass through 2mm sieve after 
3
which they were weighed in duplicate and transferred to 250 cm  Erlenmeyer flasks. 
3
Exactly 10 cm  of 1 M potassium dichromate (K2Cr2O7) was pipetted into each flask 
3
and swirled gently to disperse the soil followed by addition of 20 cm  of concentrated, 
sulphuric acid. The flask was swirled gently until soil and reagents were thoroughly 
mixed. The mixture was then allowed to stand for 30 minutes on a glass plate to allow 
3
for the oxidation of potassium dichromate to chromic acid. Distilled water (100 cm ) 
was added followed by addition of 3-4 drops of ferroin indicator, after which the 
61 
 
 
mixture was titrated with 0.5M ferrous sulphate solution ((NH4)2SO4Fe). A blank 
titration (without 1 g of soil) was similarly carried out. The % organic carbon is given 
by the following equation: 
%TOC = M1e1 K2Cr2O7 – M2e2FeSO4 x 0.0031 x 100 x F 
                             Sample Weight (air dried soil)  
F = Correction factor (1.33) 
M1 = mole of K2Cr2O7 
e1 = volume of K2Cr2O7 
M2 = mole of FeSO4 
             e2 = volume of FeSO4 
% Organic matter in soil = % Organic carbon x 1.729 (Bamgbose et al, 2000). 
                3.3.2.11 Total Extractable petroleum Hydrocarbon (TPH)  
 
One gram (1.0 g) of each soil sample was put into a 500 mL volumetric flask and 
to this was added 200 mL of xylene. The xylene/soil mixture was shaken vigorously for 
five minutes and filtered into 400 mL cylinder. The volumetric flask and solid materials 
were rinsed properly with 500 mL xylene and filtered again into the cylinder. Total 
petroleum hydrocarbon content (TPH) in the xylene/hydrocarbon mixture was 
thereafter determined by photometric method using Electrophotometer at a wavelength 
of 425 nm. TPH was estimated from a calibration curve, obtained by measuring 
absorbance of a standard prepared in 2.5, 5.0, 10.0, 20.0, 25.0 and 30  (Osuji and 
Adesanya, 2005) 
  3.4 Field study on earthworm distribution and abundance 
This investigation was carried out through two years (April, 2007 – March, 2009).  
Based on nearness to point of pollution and impact of inferno, samples were collected 
100 m within epicenter of spill and 500 m away from spill. Twenty topsoil samples 
(0.5mx0.5mx0.2m) were collected randomly from the epicenter of the spill and 500 
meters away from the spill for earthworms. Earthworms were collected by hand 
sorting method into plastic bottles containing Formoacetoalcohol (FAA), (Owa et al, 
2004). It was ensured that whole earthworms including adults and juveniles 
earthworms were collected (ISO Protocol, 2005) and were then taken to laboratory for 
onward enumeration and identification. Sampling was done monthly through seasons 
62 
 
 
so as to monitor the effect of seasonal variation on earthworm abundance and 
distribution. 
Earthworms for each quadrat throw were first sorted out into species and based on 
maturity (adults and juveniles), they were then enumerated and recorded. The 
earthworms were identified following the original descriptions (Beddard 1891; Rosa 
1896, Sims 1971) with the assistance of the earthworm taxonomist, Prof. S.O. Owa of 
Olabisi Onabanjo University, Ago-Iwoye. 
 3.5 Determination of levels of contaminants in earthworm species  
   The concentration of metals in the abundant earthworm species, were carried out. 
o
Samples of the earthworm species were collected and kept in the freezer at 4 C prior to 
heavy metal analyses. Heavy metals (Mn, Cu, Zn, Pb, Cd, Cr, V and Ni) concentrations 
were determined using atomic absorption spectrophotometry. 3g of thawed earthworm 
samples were weighed and digested with 2ml concentrated nitric acid and heated to 
dryness on a hotplate. The digest was redissolved in 1ml concentrated nitric acid after 
which it was made up to 50ml with distilled water. Heavy metal analysis was done with 
atomic absorption spectrophotometer (Schimazo model 2380),  (Bamgbose et al, 2000).  
3.6 Sensitivity test  
             3.6.1 Test animal and soil preparation 
 
 Similar indigenous earthworm species in Agaye soil were collected by hand 
picking from a garden soil in Ring road, Ibadan. The earthworms were collected from 
the same site in order to reduce variability in biotype. Earthworms were brought into 
the laboratory in plastic buckets containing soil collected from the same garden soil 
and supplemented with half-boiled, ground water-leaf (Talinium triangulare) (Fafioye 
and Owa, 2000) and then moistened with distilled water. They were left to acclimatize 
for 7 days. Subsequently, earthworm  were fed with leaflets of lettuce Nymphea lotus, 
3g per 10 worms every 4days throughout the period of all studies carried out 
(Otitoloju, 2005). Adult earthworms were picked and used for the sensitivity tests in 
order to determine the earthworms‟ tolerance to the contaminated soil. 
63 
 
 
Soil preparation was done according the method adopted by Otitoloju (2005) 
with slight modifications. Loamy soil sourced from the same garden was air-dried, 
ground and sifted through a 0.30mm (mesh size) screen so as to standardize the grain 
size. One kilogram (1kg) portion of the prepared soil moistened with 5ml of distilled 
water was prepared and put into Plastic vessel with size 20cm in diameter (base) by 
35cm height and 35cm in diameter (top), the bottom was perforated while the top was 
covered with mesh and made to stay with elastic bands. This soil was used as control 
and designated NS. 1kg of fresh soil from Agaye community was also prepared as 
described above and designated CS.  
A survival and avoidance test for the two most abundant earthworms in soil 
sample from Agaye was carried out in October, 2008 and repeated in October, 2009.   
             3.6.2      Fourty – eight hours (48h) Avoidance Test 
 
A two chambered test system was used (Schaefer, 2001). 1 kg of contaminated soil 
(CS) from Agaye settlement was applied to one chamber of the system and another 1 
kg of non-contaminated soil (NS) was then applied to the second chamber of each 
system; the two chambers were entirely separated so as to prevent mixing up of both 
soil types. The separator was then removed thereby creating a groove in between both 
soil types; this was done to allow free movement of earthworms between the two 
chambers. Ten earthworms each were added to the groove of each set-up. Each 
chamber was covered with mesh and made to stay with the aid of elastic band and left 
for 48hrs. Prior to counting, the separator was put back in place (in groove), each soil 
type removed separately and the number of earthworms in each chamber was counted 
after 48hrs and recorded.  
             3.6.3  Seven days Survival Test  
 
Ten earthworms were applied to each set – up described above (i.e. CS and NS 
in a plastic bucket) and this was done in triplicate. Set-up was arranged in a 
randomized block design. The vessels were thereafter covered with meshes which 
were kept in place by elastic band. The number of surviving earthworms in both soils 
was observed and recorded 1day, 2days, 5days and 7-day period.  
64 
 
 
Based on the result from the sensitivity test, an ex-situ bioremediation was done in 
2009. 
            3.7   Experimental set-up for bioremediation study 
The bioremediation study was carried out to monitor the TPH and heavy 
metals (Pb, Mn, Zn, Ni, Cd, Cr, V and Cu) levels in the soil over a 12 weeks period. It 
was carried out to test the effectiveness of the most abundant indigenous earthworm in 
remediation. The experiment was set up according to the description by Hickman and 
Reid (2008) with slight modifications. Contaminated soil from Agaye (CS) and non-
contaminated soil samples (NS) were collected, macerated and sieved with mesh of 
size 5mm and mixed thoroughly. The soils were distributed into pots (30cm diameter x 
45cm height) in triplicates and arranged in the plot design (Table 3.3 and Fig. 3.2).  
Plastic piping (5mm diameter) was inserted into the soil and three holes were 
drilled in the base of the pots, this was to aerate the treatments for 15mins every 24hrs. 
Further manual stirring of set up was not done so as to ensure aeration to be potentially 
due to the presence of earthworm activities (burrowing and bioturbation). Before soils 
were applied into pots, washed gravel 3cm thick were laid in the base of each pot (to 
promote uniform air dissipation). The gravel was then covered with plastic mosquito 
net cut to size that allowed air to percolate up from the base and prevent the migration 
of earthworms into gravel (Zachery and Reid, 2008a).  
             3.7.1 Earthworm application 
Soil was rehydrated and manually mixed into the plastic pots. Mass of 
contaminated soil (70% maximum water holding content - WHC) was kept constant at 
2kg wet weight/vessel. Adult earthworms were left to acclimatize for one week and 
allowed to depurate for 24h prior to use. Five earthworms per kg of material were 
added to each of the required treatments and quadruplicates. The earthworms were 
applied and the surfaces of the vessels were covered with plastic mesh. Water was 
added periodically to maintain levels at 70% maximum WHC. The following were 
monitored and data collected over the period. Heavy metals (Pb, Mn, Zn, Ni, Cd, Cr, 
V and Cu) and Total Petroleum Hydrocarbon (TPH) were analysed as scheduled in 
Table 3.4. 
65 
 
 
                      
 
                               
                                Table 3.3: Experimental set-up for bioremediation study 
 
   Row 1 Row 2 Row 3 
CS+E  CS NS 
 
 
 NS CS+E  CS 
 
 CS NS CS+E  
 
 
 
 
Key: Contaminated Soil (CS), Earthworm (E) , Non-contamianted Soil and Earthworm 
(NSE)and Control (NS) 
  
 
 
 
 
 
 
 
66 
 
 
 
                                                                                                                                                                                                                               
                    Fig.3.2 Picture of experimental set-up for bioremediation study 
 
 
 
 
 
67 
 
 
 
Table 3.4: A modified Small-Scale Bioremediation Sampling Plan 
Sampling period                                                             Analysis done 
 1 2
Pretreatment Sampling                                             TPH  and Heavy metals  
after 6 weeks                                                             TPH  and Heavy metals 
End of Season – 12 weeks                                        TPH  and Heavy metals  
 
Source: New York State Dept of Environment Conservation Protocol (1996) 
    (1) TPH analysis was performed using gravimetric method. 
               (2) Indicator compounds analyzed were Cr, Cd, Pd, Zn, Cu, Mn, Ni and V using    
                   Atomic Absorption Spectrophotometer (AAS) 
* The recommended protocol for bioremediation study requires carrying out microbial counts and    
    Nutrient  analyses (N,P and K). However, it was carried out in this study  
       
 
 
 
 
 
 
 
 
 
 
68 
 
 
 
3.8 Statistical Analysis  
Earthworm diversity and abundance were analysed using Shannon Weiner (H) 
and Mann-Whitney respectively while data on physicochemical parameters were 
subjected to correlation, student t-test and ANOVA at p≤0.05 using spss version 16.0. 
Results were presented in means and standard deviation.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
69 
 
 
                                                        CHAPTER FOUR 
   4.0                                                       RESULTS 
4.1  Heavy metal concentrations in water samples  
The monthly mean concentration of V, Ni, Mn, Cu, Zn, Pb, Cd and Cr in ground 
water samples (GW1 – GW5) between June, 2007 and April, 2009 is shown in Fig. 
4.1. Chromium, cadmium, and lead showed reduction over the period of study 
whereas zinc, copper, manganese, nickel and vanadium increased over the period of 
study. The result showed that Zinc concentration ranged from 0.54–0.99mg/ and Ni 
concentrations ranged from 0.16-1.59mg/l. The concentrations of Chromium, 
Cadmium and Lead were lowest having concentrations < 0.2mg/l. 
The mean concentrations of V, Ni, Mn, Cu, Zn, Pb, Cd and Cr in surface water 
samples (SW1 and SW2) showed that concentrations of most heavy metals were 
highest in the months of June and August (rainy season) and lowest between 
December and February (dry season). Manganese, Copper and Zinc had maximum 
concentrations of 9mg/l, 6.2mg/l and 6.1mg/l respectively while Lead, Cadmium and 
Chromium showed the lowest concentrations of <1mg/l (Fig. 4.2).  
The mean concentrations of heavy metals in all water samples compared with 
WHO/NESREA standards are shown in Table 4.1. Cd, Pb, and Ni of well water 
samples had concentrations higher than the WHO/NESREA recommended limit for 
drinking water; also Cd, Cu and Ni of surface water sample were higher than the 
WHO/NESREA permissible limit for surface water. Mean concentrations of heavy 
metals (V, Ni, Mn, Cu, Zn, Pb, Cd and Cr) concentration in water samples from each 
sampling point are shown in Table 4.2.  
 
 
70 
 
 
1.8
1.6
1.4
1.2
Cr
1 Cd
Pd
0.8 Zn
Cu
0.6
Mn
Ni
0.4
V
0.2
0
Time
 
 
 
Fig 4.1 Temporal variation of the heavy metal profile for ground water (GW1 and GW5) 
 
Keys:  
Cd=Cadmium 
 Pb=Lead  
Zn=Zinc  
Cu=Copper  
Mn=Manganese 
 Ni=Nickel 
V=Vanadium 
 
 
 
 
 
 
 
 
71 
 
Each metal level (mg/l)
 
10
9
8
7
Cr
6
Cd
Pd
5
Zn
4 Cu
Mn
3
Ni
2 V
1
0
Jun-07 Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr '09
Time
 
 
Fig. 4.2 Temporal variation of the heavy metal profile for surface water (SW1 and SW2) 
 
Keys:  
Cd=Cadmium 
 Pb=Lead  
Zn=Zinc  
Cu=Copper  
Mn=Manganese 
 Ni=Nickel 
V=Vanadium 
 
 
 
 
 
 
 
 
72 
 
Each metal level (mg/l) 
 
Table 4.1: Mean concentrations of heavy metals in water samples compared with 
WHO/NESREA standards 
Metals Well water  Well water WHO/NESREA SW ± SD WHO/NESREA 
Ctrl ± SD  drinking/ (mg/l) Surface water 
(mg/l)  standard standard  
 (mg/l) (mg/l) 
Cr 0.04±0.03  0.04±0.03  0.05/0.5  0.04 ± 0.03 -/ 0.5  
Cd 0.05±0.04  0.03 ± 0.03  0.003/0.001 0.03 ± 0.03 <0.0004 /0.005  
Pb 0.04±0.04  0.03 ± 0.03  0.01/0.2  0.05 ± 0.05 - / 0.1  
Zn 0.79±0.67  0.59 ± 0.41  3.0/3.0  0.88 ± 1.03 <10 μg/litre / 
0.02  
Cu 0.22±0.17  0.17 ± 0.08  1.00 /1.00 0.23 ± 0.24 0.036/ 0.001  
Mn 0.19±0.07  0.19 ± 0.07  0.4/0.2  0.15 ± 0.07 - / 40 
Ni 0.98±0.81  0.26 ± 0.24  0.01/0.1  2.18 ± 0.44 <0.1  
V 0.22±0.13  0.12 ± 0.08  -  0.26 ± 0.05 - 
 
Keys:  
Cd=Cadmium 
 Pb=Lead  
Zn=Zinc  
Cu=Copper  
Mn=Manganese 
 Ni=Nickel 
V=Vanadium 
 
 
 
 
 
 
 
 
 
73 
 
 
Table 4.2: Monthly mean concentrations of heavy metals in water samples from each sampling points 
    CODE Cr (mg/l) Cd (mg/l) Pd (mg/l) Zn (mg/l) Cu (mg/l) Mn (mg/l) Ni (mg/l) V (mg/l) 
GW1 0.04±0.03 0.03±0.04 0.03±0.03 0.67±0.36 0.21±0.14 0.18±0.07 0.62±0.36 0.20±0.04 
GW2 0.03±0.02 0.02±0.04 0.02±0.01 0.65±0.39 0.21±0.11 0.16±0.07 0.51±0.39 0.17±0.07 
GW3 0.05±0.05 0.03±0.03 0.03±0.03 0.51±0.26 0.17±0.11 0.18±0.07 0.29±0.14 0.22±0.22 
GW4 0.02±0.01 0.03±0.01 0.06±0.06 0.17±0.08 0.13±0.06 0.20±0.15 0.13±0.24 0.18±0.03 
GW5 0.05±0.02 0.03±0.03 0.04±0.03 0.54±0.34 0.15±0.09 0.17±0.02 0.83±0.62 0.25±0.09 
GW6 0.04±0.03 0.03±0.03 0.03±0.03 0.59±0.41 0.17±0.08 0.19±0.07 0.26±0.24 0.12±0.05 
SW1 0.04±0.03 0.04±0.01 0.05±0.03 0.30±0.10 0.10±0.02 0.11±0.33 1.81±0.23 0.26±0.04 
SW2 0.04±0.03 0.03±0.03 0.05±0.06 1.08±1.13 0.28±0.26 0.17±0.07 2.30±0.43 0.26±0.05 
WHO/NESREA 0.05/0.5 0.003/0.001 0.01/0.2 3.0/3.0 1.00 /1.00 0.4/0.2 0.01/0.1 - 
drinking 
standard 
WHO/NESREA -/ 0.5 <0.0004 -- -/ 0.1 <10μg/ 0.036/ - / 40 <0.1 - 
Surface water /0.005 litre / 0.02 0.001 
standard  
Keys: 
GW1 = Well 1         GW2 = Well 2               GW3 = Well 3           GW4 = Well in school premises       GW5 = Borehole in school 
premises         GW6=Control   SW1=Surface water 1   SW2= Surface water2  
74 
 
 
4.2 Concentration of sulphate, nitrate, phosphate and TPH in water samples over 
study period 
The mean concentrations of sulphate, nitrate, phosphate, pH, temperature, TDS, TH, 
alkalinity, conductivity and chlorine are shown in table 4.3 while the monthly 
variation of sulphate, nitrate and phosphate in water samples are presented in fig. 4.3.  
The Mean concentrations of sulphate, nitrate, phosphate in water samples compared 
with WHO/NESREA standard are shown in Table 4.4. All concentrations for well 
water samples fell within the WHO/NESREA standard for drinking water. The means 
of physicochemical parameters (pH, Temperature, Total Dissolved Solids, Total 
hardness, Alkalinity, Conductivity and Chlorine) in water samples compared with 
WHO/NESREA standards are presented in Table 4.5. In well water samples, pH fell 
below the WHO/NESREA recommended limit while temperature was above the 
WHO/NESREA limit for drinking water; all other parameters were within the 
recommended WHO/NESREA limit for drinking water.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
75 
 
 
 
 
           Table 4.3 Monthly mean concentrations of sulphate, nitrate, phosphate, pH, Temperature, Total Hardness, Alkalinity and Conductivity in     
                            water samples 
Stations Sulphate Nitrate Phosphate pH Temperature TDS TH Alkalinity Conductivity 
c
(mg/l) (mg/l) (mg/l) (0 )  (mg/l) (mg/l) 
GW1 0.11±0.04 0.11±0.04 0.1±0.05 5.71±0.35 26.85±1.33 241.37±388.20 118.96±68.80 13.37±6.35  32.41±18.30 
GW2 0.09±0.03 0.13±0.05 0.1±0.05 5.98±0.9 26.95±1.67 274.15±403.37 137.05±75.25 10.94±5.78 43.09±36.21 
GW3 0.11±0.05 0.09±0.04 0.12±0.04 6.45±0.29 27.06±1.37 218.61±91.11 132.01±85.93 15.12±10.37 39.74±13.39 
GW4 0.05±0.01 0.04±0.01 0.07±0.09 5.46±0.38 25.63±0.95 86.27±49.78 91.25±86.23 3.37±2.20 57.91±22.38 
GW5 0.1±0.05 0.1±0.06 0.14±0.09 5.81±0.6 26.71±1.42 251.53±466.86 115.71±86.25 9.93±7.27 56.89±20.63 
CW6 0.16±0.04 0.18±0.06 0.09±0.04 6.10±0.69 27.09±1.63 256.92±249.30 133.97±103.01 6.96±5.77 17.49±3.89 
SW1 0.06±0.02 0.03±0.01 0.07±0.02 5.43±0.24 26.50±1.00 61.86±47.51 109.70±47.87 3.07±2.51 90.56±112.98 
SW2 0.11±0.04 0.08±0.05 0.11±0.05 5.23±0.43 26.47±2.00 158.92±168.92 127.93±54.36 4.19±3.16 36.33±19.59 
 
Keys: 
GW1 = Well 1         GW2 = Well 2               GW3 = Well 3           GW4 = Well in school premises       GW5 = Borehole in school 
premises         GW6=Control   SW1=Surface water 1   SW2= Surface water2  
 
 
 
 
 
76 
 
 
 
0.25
0.2 GW1
GW2
0.15
GW3
0.1 GW4
GW5
0.05
GW6
0 SW1
Jun'07 Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr'09
SW2
Time
 
0.3
GW1
0.25
GW2
0.2
GW3
0.15
0.1 GW4
0.05 GW5
0 GW6
Jun'07 Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr'09 SW1
Time SW2
 
0.3
0.25 GW1
0.2 GW2
GW3
0.15
GW4
0.1
GW5
0.05
GW6
0
SW1
Jun'07 Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr'09
SW2
Time
 
Fig. 4.3 Mean monthly variation of sulphate, nitrate and phosphate in water samples 
Keys for sampling points: 
GW1 = Well 1,                                      GW2 = Well 2                                   GW3 = Well 3 
GW4 = Well in school premises           GW6=Control                                    SW1 = Wet land 1 
SW2= Wetland  
77 
 
Conc. of phosphate (mg/l) Conc. of nitrate (mg/l) Conc. of  sulphate (mg/l)
 
Table 4.4  Mean concentrations of sulphate, nitrate, phosphate in water samples 
compared with WHO/NESREA standard 
 
 
Parameter Well Well water WHO/NESREA Wet Land   
water Ctrl ± SD drinking water       ± SD 
standard 
(mg/L) 
-
SO (mg/l) 0.13± 0.04 0.16 ± 0.05 250 /200 0.09 ±0.04  
4
-
NO (mg/l) 0.11± 0.05 0.13 ± 0.06 20/45 0.07 ±0.005  
3
-
PO (mg/l) 0.13±0.05 0.09 ± 0.09 <5/- 0.10 ±0.005  
4      
      
TPH (mg/l) 1.34±0.64 0.64±0.26 - /- 3.30±0.54  
 
 
 
 
- 
Keys: SO4 = Sulphate,  
-
          NO3  = Nitrate,  
-
          PO4  = Phosphate and   
          TPH =Total petroleum hydrocarbon 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
78 
 
 
Table 4.5 Mean concentrations of other physicochemical parameters in water samples 
compared with WHO/NESREA standards 
 
Parameter  Well  Well water (Ctrl)  WHO/NESREA Wet land  
water  drinking water  
standard  
     
pH  5.88±0.63  6.10 ± 0.69  6.50-9.50  5.28 ± 1.78  
     
0
Temp ( C)  27.1±1.76  27.09 ± 1.63  25.00  26.48 ± 1.78  
     
TDS (mg/l)  195±157              256.43 ± 249.30                  500       134.65 ±152. 51  
     
TH (mg/l)  141±83.5             133.97 ± 103.01 -         123.38 ± 51.88  
Alk.  11.2±7.94  6.96 ± 5.77  -  3.89 ± 3.08  
Cond. (ohms)  58.1± 80.86  42.78 ± 48.56  -  56.90 ± 73.23  
-  
        Cl (mg/l)  33.4±14.6                17.49 ± 3.89                  <250  49.89 ± 58.50  
 
 
 
 
Key: Temp= Temperature                                             Cond= Conductivity 
         TDS= Total dissolved solute                                  Cl = Chlorine 
         TH= Total Hardness                                               Alk= Alkalinity 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
79 
 
 
4.3 Heavy metal concentration in soil samples  
The mean concentrations of heavy metals (V, Ni, Mn, Cu, Zn, Pb, Cd and Cr) in 
soils from sampling points are shown in Fig 4.4 Manganese had the highest 
concentration recorded during the rainy season. The mean concentrations of heavy 
metals in soils from wetland showed that most were highest in month of August for 
both years of study and lowest between December and February. Manganese and 
Nickel recorded the highest concentration with a maximum concentration of 8.99 mg/l 
and 6.05 mg/l respectively while Chromium, Cadmium and Lead, showed the lowest 
concentration of 0.35 mg/l, 0.17 mg/l and 0.14 mg/l recorded during this study (Fig 
4.5). The monthly heavy metal (V, Ni, Mn, Cu, Zn, Pb, Cd and Cr) levels in soils for 
each sampling point are shown in Table 4.6. The mean concentrations of heavy metals 
in soil samples compared with control soil are shown in Table 4.7. All heavy metal 
concentrations except Cr were lower than the control sample.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80 
 
 
14
12
10
Cr
8 Cd
Pd
Zn
6
Cu
Mn
Ni
4
V
2
0
Jun'07 Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr'09
Time
 
Fig.4.4     Mean concentrations of heavy metals in soil samples between June 2007 and April 
2009. 
 
Keys:  
Cd=Cadmium 
 Pb=Lead  
Zn=Zinc  
Cu=Copper 
Mn=Manganese 
 Ni=Nickel 
V=Vanadium 
 
 
81 
 
Heavy metal levels (mg/l)
 
10
9
8
7
Cr
6 Cd
Pd
5
Zn
4
Cu
3 Mn
Ni
2
V
1
0
Jun-07 Aug Oct Dec Feb Apr jun Aug Oct Dec Feb Apr
Time
 
Fig.4.5     Mean concentrations of heavy metal in soils from wetland between June 2007 and 
April 2009. 
Keys:  
Cd=Cadmium 
 Pb=Lead  
Zn=Zinc  
Cu=Copper 
Mn=Manganese 
 Ni=Nickel 
V=Vanadium 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82 
 
Heavy metal concentrations (mg/kg)
 
 
 
 
 
 
Tab. 4.6 Mean concentrations of heavy metals in soil samples from each sampling points 
 
Stations Cr Cd Pb Zn Cu Mn  Ni           V              
(mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) 
S1 0.15±0.06 0.08±0.04 0.1±0.04 5.25±4.83 2.81±1.69 4.29±2.02 1.53±0.43 0.26±0.17 
S2 0.15±0.09 0.07±0.04 0.13±0.02 3.70±1.66 2.69±2.83 10.07±4.64 1.18±0.1 0.24±0.08 
S3 0.15±0.1 0.1±0.04 0.15±0.07 2.70±1.50 2.81±1.44 8.18±4.30 0.92±0.43 0.22±0.10 
S4 0.13±0.6 0.1±0.05 0.12±0.02 2.73±1.41 2.84±1.53 7.68±4.06 1.42±0.35 0.27±0.14 
S5 0.14±0.07 0.08±0.03 0.14±0.04 2.85±1.71 2.20±1.52 5.64±2.91 3.11±2.54 0.26±0.11 
S6 0.14±0.14 0.12±0.05 0.12±0.06 2.70±1.36 1.76±2.03 6.36±4.13 2.74v2.37 0.24±0.06 
Sv1 0.13±0.08 0.08±0.04 0.11±0.04 2.90±1.45 1.95±1.69 5.44±2.29 2.18±1.90 0.29±0.17 
Sv2 0.16±0.12 0.1±0.05 0.1±0.05 2.66±1.35 2.08±1.80 8.16±3.20 1.91±1.70 0.25±0.1 
Keys for sampling points: 
 
S1= Soil sampled within loci of well 1 
S2= Soil sampled within loci of well 2 
S3 = Soil sampled within loci of well 3 
S4 =Soil sampled within loci of well in school 
S5=Soil sampled within loci of bor hole 
S6 =Soil sampled within loci of well 6 
Sv1 = Soil sampled within loci of wetland 1 
Sv2 =Soil sampled within loci of wetland 2 
 
Keys for metals:  
 
Cd=Cadmium, 
 Pb=Lead,  
Zn=Zinc,  
Cu=Copper,  
Mn=Manganese, 
 Ni=Nickel 
V=Vanadium 
83 
 
 
 
 
Table 4.7: Mean concentrations of heavy metals and TPH in soil samples compared with 
control (June 2007 – April 2009) 
Metals Soil Wet land Control P value Significance 
samples samples samples 
(S1-S5) (SW1 and SW2) (S6) 
 
Cr 0.14±0.07 1.4±0.08 0.14±0.08 0.73 >0.05 
 
 
Cd 0.09±0.04 0.1±0.04 0.1±0.45 0.25 >0.05 
 
 
Pb 0.13±0.04 0.11±0.05 0.14±0.08 0.4 >0.05 
 
 
Zn 3.45±2.69 2.80±1.38 2.66±1.35 0.35 >0.05 
 
 
Cu 2.68±1.83 1.86±1.83 2.08±1.8 0.15 >0.05 
 
 
Mn 7.2±4.14 5.9±3.3 8.16±3.2 0.21 >0.05 
 
 
Ni 1.61±1.33 2.46±2.11 1.91±1.7 0.1 >0.05 
 
 
V 0.25±0.12 0.26±0.13 0.25±0.1 0.91 >0.05 
 
 
TPH 1.33±0.5 2.96±0.56 0.67±0.31 0.00 <0.05 
 
 
 
 
 
 
 
 
 
 
84 
 
 
 
4.4  Other physicochemical parameters in soil samples  
              Table 4.8 shows the mean concentrations of the mean concentrations of sulphate,    
              nitrate, phosphate, pH, Potassium, Sodium, Calcium, T0C, TOM and TPH in soil 
samples, the mean TPH level ranged between 1.17 – 2.03 mg/g, TOC ranged between 
0.95 – 1.36 mg/g and TOM ranged between 1.64 - 2.34 mg/g.  
 
4.5 Soil / Weather conditions of the study area 
O O
Soil temperature ranged from 21.3 C – 28.5 C while the atmospheric 
 O  O
temperature ranged from 23 C – 33 C. The soil moisture content at 15cm – 20cm 
depth ranged between 15.0 – 65.0 percent in the study area during the study period 
(Table 4.9). The soil temperature, soil moisture and rainfall showed seasonal 
fluctuations.  
Rainfall measurement used in this study was adapted from Nigeria 
meteorological agency (NIMET) weather records. There were two major seasons; the 
rainy season, with the heaviest rainfall from April to July which continued in 
October and November. There was a brief relatively dry spell in August and 
September and a longer dry season from December to March. The highest and lowest 
rainfall of 442.7mm and 0.8mm were recorded during July 2008 and Jan, 2008 
respectively in the study area (Table 4.10). 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
85 
 
 
Table 4.8: Monthly mean concentrations of Total Organic Carbon, Total Organic Matter, 
Total    
-
                Petroleum Hydrocarbon, sulphate, nitrate and phosphate  in soil samples  
                (June, 2007 – Apr 2009) 
SO4- NO3- PO4- TOC TOM TPH    
(mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg)
Jun 0.12±0.05 0.15±0.03 0.12±0.03 1.36±0.75 2.34±1.29 2.03±1.2
Aug 0.14±0.05 0.15±0.03 0.11±0.05 1.24±0.61 2.15±1.05 1.98±1.15
Oct 0.12±0.04 0.1±0.04 0.12±0.09 1.16±0.59 1.99±1.03 1.92±1.08
Dec 0.08±0.02 0.08±0.03 0.06±0.03 1.13±0.53 1.94±0.95 1.87±1.06
Feb 0.09±0.05 0.08±0.04 0.07±0.04 0.97±0.43 1.68±0.75 1.69±0.97
Apr 0.12±0.04 0.1±0.02 0.1±0.04 0.95±0.43 1.63±0.75 1.61±0.91
Jun 0.23±0,02 0.21±0.05 0.59±0.13 2.25±0.67 3.87±1.15 1.59±0.9
Aug 0.2±0.06 0.19±0.07 0.32±0.12 2.05±0.77 3.53±1.32 1.46±0.82
Oct 0.23±0.05 0.21±0.09 0.19±0.01 1.87±0.45 3.23±0.77 1.42±0.84
Dec 0.25±0.07 0.2±0.07 0.21±0.04 1.33±0.4 2.29±0.7 1.31±0.83
Feb 0.2±0.13 0.14±0.11 0.07±0.06 1.01±0.21 1.74±0.37 1.24±0.81
Apr 0.21±0.13 0.14±0.11 0.07±0.05 0.95±0.24 1.64±0.41 1.17±0.79
 
TOC = Total Organic Carbon,  
TOM = Total Organic Matter 
TPH = Total Petroleum Hydrocarbon  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
86 
 
 
 
                  Table 4.9: The mean concentrations of sulphate, nitrate, phosphate, pH, Potassium, Sodium, Calcium, T0C, TOM and 
THC in soil   
                                    samples 
Stations Sulphate Nitrate Phosphate pH Potassium Sodium Calcium TOC TOM THC 
(mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) 
S1 0.14±0.07 0.1±0.05 0.14±0.14 6.05±0.32 0.09±0.01 0.04±0.01 2.10±0.16 1.01±0.29 1.76±0.49 1.11±0.19 
S2 0.21±0.11 0.17±0.06 0.18±0.05 6.70±0.58 0.09±0.01 0.04±0.01 2.14±0.08 1.02±0.20 1.77±0.35 1.20±0.18 
S3 0.16±0.1 0.18±0.1 0.16±0.05 6.30±0.56 0.09±0.01 0.04±0.01 2.14±0.09 1.15±0.49 1.99±0.84 0.89±0.23 
S4 0.17±0.05 0.11±0.05 0.17±0.05 5.52±0.38 0.09±0.01 0.04±0.01 2.31±0.18 1.40±0.71 2.45±1.28 2.08±0.32 
S5 0.18±0.05 0.15±0.04 0.08±0.02 6.08±0.67 0.09±0.01 0.07±0.09 2.24±0.12 1.43±0.60 2.64±0.99 1.38±0.42 
S6 0.13±0.05 0.08±0.02 0.18±0.05 6.01±0.70 0.08±0.02 0.04±0.01 2.24±0.18 1.77±0.76 3.05±1.31 3.03±0.40 
Sv1 0.15±9.11 0.08±0.02 0.12±0.03 5.71±0.57 0.09±0.02 0.04±0.01 2.20±0.17 1.37±0.77 2.20±1.32 2.90±0.70 
Sv2 0.17±0.08 0.09±0.03 0.2±0.06 5.82±0.46 0.08±0.02 0.05±0.01 2.07±0.13 1.64±0.77 2.82±1.32 0.67±0.31 
 
Keys: 
S1 =Soil sample around GW1              S2 = Soil sample around GW2               S3 = Soil sample around GW3          S4 = Soil sample 
around GW4       S5 = Soil sample around GW5             Sv1= Soil sample around GW6              Sv2= Soil sample around SW2  
 
87 
 
 
   Table 4.10: Monthly average rainfalls, temperatures and Relative humidity in Lagos area 
Months Rainfall in Ave. air temp Relative 
o
area (mm) ( C) Humidity  
June ‘07 367.7 25.9 90 
July ‘07 228 25.7 88 
Aug ‘07 287.9 25.4 88 
Sept ‘07 156.7 25.8 89 
Oct ‘07 120.3 26.3 87 
Nov ‘07 118.3 27.3 85 
Dec ‘07 5.4 27.4 83 
Jan ‘08 0.8 26.6 66 
Feb ‘08 3.3 28.6 74 
March ‘08 69.6 28.5 81 
April ,08 96.8 28.5 81 
May ‘08 230 27.3 86 
June ‘08 365 26.2 89 
July ‘08 442.7 25.5 91 
Aug ‘08 134.3 25.6 88 
Sept ‘08 226.8 26 89 
Oct ‘08 98.8 26..6 88 
Nov ‘08 98.9 27.8 85 
Dec ‘08 49 27.8 82 
Jan ‘09 1.6 27.9 79 
Feb ‘09 16.3 28.7 81 
March ‘09 33.9 29.0 81 
April ,09 115.5 28.0 83 
 
                      Adapted from Nigerian meteorological agency (NIMET), 2014 
 
 
 
 
 
88 
 
 
 
4.6 Earthworm abundance and distribution 
 
        The species of earthworms encountered during the study period were Lybiodrillus 
violaceous, Dichogaster modiglanin, Ephyriodrilus afroccidentalis and Heliodrillus 
lagosensis. Fig 4.6 shows the total earthworm species in epicenter and 500m away 
from spill. L. violaceous was the most abundant followed by D. modigliani within 
epicenter and 500m away from the spill. The monthly abundance of earthworm 
species and their weights within epicenter and 500m away is presented in table 4.11-
4.14, E. afroccidentalis and H. lagosensis were only encountered in the second year of 
study. 
Mann-Wittney analysis comparing population size of earthworm species in the 
epicentre and 500m away from the spill determined in the first year indicated that 
there was a significant difference in size between the two sites (P= 0.07: P < 0.1). 
However, in the second year there was no significant difference between the two sites 
(P= 0.229; P > 0.1). L.violaceous was identified to be the most abundant earthworm 
spp found within Agaye community. The Shannon-Wiener diversity Index showed 
that in the first year, H = 0.2813; while in the second year, H = 0.7315. This indicated 
that there was more earthworm species diversity in the second year compared to the 
first year in the study area.  
 
89 
 
 
2500
2000
1500
500m away
1000 Epicenter
500
0
LV DM HL EA
Species of earthworms  
 Keys: L.V= Lybiodrillus violaceous, D.G= Dichogaster modiglanin, 
                  E.A= Ephyriodrillus afroccidentalis, H.L= Hiliodrillus lagosensis 
     
Fig. 4.6   Total earthworm species in epicenter and 500m away from spill 
 
 
 
 
 
 
 
 
90 
 
Number of earthworms
 
            Table 4.11 Monthly number of earthworm species found in the epicentre of spill  
 
 Months LV DS HL EA TOTAL 
 No. 
 Jun’07 18 0 0 0 18 
   J  u   l y  ’ 0  7   29 0 0 0 29 
 Aug’07 33 0 0 0 33 
 Sept’07 48 0 0 0 48 
 Oct’07 43 0 0 0 43 
 Nov’07 27 0 0 0 27 
 Dec’07 5 0 0 0 5 
 Jan’08 * * * * * 
 Feb’08 * * * * * 
 Mar’08 * * * * * 
 Apr’08 16 2 0 3 21 
 May’08 21 3 0 2 25 
 Jun’08 68 2 0 0 70 
 July’08 98 1 0 3 102 
 Aug’08 122 3 0 1 130 
 Sept’08 157 3 1 2 163 
 Oct’08 178 5 2 4 189 
 Nov’08 57 1 1 3 62 
 Dec’08 23 0 0 0 23 
 Jan’09 8 0 0 0 8 
 Feb’09 6 0 0 0 6 
 Apr’09 11 0 0 0 11 
 
 
 
 
Keys: L.V= Lybiodrillus violaceous, D.G= Dichogaster modigliani, 
                              E.A= Ephyriodrillus afroccidentalis, H.L= Hiliodrillus lagosensis 
    = Not done 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
91 
 
 
                   Table 4.12: Weight of earthworm species found in the epicentre of spill  
 
 
 
 Months LV DS HL EA TOTAL 
 (g) (g) (g) (g) WGT (g) 
 Jun’07 3.32 0 0 0 3.32 
 July’07 23.89 0 0 0 23.89 
 Aug’07 11.91 0 0 0 11.91 
 Sept’07 43.03 0 0 0 43.03 
 Oct’07 46.8 0 0 0 46.8 
 Nov’07 22.17 0 0 0 0 
 Dec’07 1.38 0 0 0 0 
 Jan’08 * * * * * 
 Feb’08 * * * * * 
 Mar’08 * * * * * 
 Apr’08 2.84 0.4 0 0.39 3.63 
 May’08 3.18 0.37 0 0.24 3.79 
 Jun’08 50.09 0.4 0 0 50.89 
 July’08 73.13 0.15 0 0.43 73.71 
                 A   u  g’08 99.09 0.34 0 0.18 99.94 
 Sept’08 124.25 0.41 0.36 0.13 124.97 
 Oct’08 138.78 0.94 0.77 0.31 139.68 
 Nov’08 43.89 0.12 0.29 0.27 44.57 
 Dec’08 3.93 0 0 0 3.93 
 Jan’09 1.41 0 0 0 1.41 
 Feb’09 1.28 0 0 0 1.28 
  Apr’09 2.06 0 0 0 2.06 
       
 
     
      Keys: L.V= Lybiodrillus violaceous, D.G= Dichogaster modigliani, 
                  E.A= Ephyriodrillus afroccidentalis, H.L= Hiliodrillus lagosensis 
     = Not done 
 
 
 
 
 
 
 
 
 
 
            
 
92 
 
 
                Table 4.13: Number of earthworm species found 500m away from the spill 
 
Months LV DS HL EA        TOTAL 
Jun’07 65 11 0 0 76 
July’07 120 9 0 0 129 
Aug’07 186 8 0 0 194 
Sept’07 198 10 0 0 208 
Oct’07 211 14 0 0 303 
Nov’07 28 9 0 0 37 
Dec’07 5 2 0 0 7 
Jan’08 * * * * * 
Feb’08 * * * * * 
May’08 * * * * * 
Apr’08 19 5 2 3 29 
May’08 89 8 0 19 126 
Jun’08 169 15 5 24 219 
July’08 204 19 3 20 320 
Aug’08 262 21 0 22 388 
Sept’08 308 20 7 18 353 
Oct’08 362 23 10 22 417 
Nov’08 * * * * * 
Dec’08 13 3 2 5 23 
Jan’09 6 0 0 0 6 
Feb’09 5 2 0 0 7 
Apr’09 16 5 0 0 21 
  
               Keys: L.V= Lybiodrillus violaceous, D.G= Dichogaster modigliani, 
                           E.A= Ephyriodrillus afroccidentalis, H.L= Hiliodrillus lagosensis 
  = Not done 
 
 
 
 
 
 
 
 
 
 
 
 
93 
 
 
                      Table 4.14: Weight of earthworm species found 500m away from the spill 
 
Months LV DS HL    EA TOTAL 
(g) (g) (g)     (g) WGT (g) 
Jun’07 18.99 0.31 0 0 19.3 
July’07 29.78 0.24 0 0 30.02 
Aug’07 41.75 0.19 0 0 41.94 
Sept’07 42.88 0.28 0 0 43.16 
Oct’07 45.62 0.82 0 0 46.44 
Nov’07 9.01 0.29 0 0 9.3 
Dec’07 1.09 0.08 0 0 1.17 
Jan’08 * * * * * 
Feb’08 * * * * * 
May’08 * * * * * 
Apr’08 3.77 0.15 0.05 0.16 4.13 
May’08 21.22 0.32 0 1.97 24.31 
Jun’08 34.2 1.44 0.17 2.27 37.93 
July’08 43.25 1.89 0.09 2.01 51.24 
Aug’08 290.27 2.15 0 2.43 304.02 
Sept’08 311.15 2.08 0.21 1.86 315.3 
Oct’08 337.81 2.79 6 10.16 350.58 
Nov’08 * * * * * 
Dec’08 2.17 0.09 0.03 0.25 2.54 
Jan’09 1.08 0 0 0 1.08 
Feb’09 1.02 0.05 0 0 1.07 
Apr’09 3.29 0.14 0 0 3.43 
 
                 Keys: L.V= Lybiodrillus violaceous, D.G= Dichogaster modigliani, 
                           E.A= Ephyriodrillus afroccidentalis, H.L= Hiliodrillus lagosensis 
             = Not done 
     
 
 
    
     
 
 
 
 
 
 
 
 
 
 
94 
 
 
 The densities of earthworm species in comparison with concentration of metals 
in the epicenter and 500 m away are shown in Fig. 4.7 – 4. 14. The trend shows that 
the heavy metal concentrations had no major influence on the fluctuations in 
earthworm species abundance. A comparison of earthworm species abundance 
between the epicentre of oil spill and 500m away from the spill in the first and second 
year are illustrated in Fig. 4.15 - 4.18.   
     The mean concentrations of metals in the two most abundant species 
(L.violaceous and D. modiglanin) are presented in Table 4.15. The mean concentrations 
of Cu, Pb and Cd for L.violaceous (mg/g) were Pb (0.41±0.02) > Cd (0.17±0.003) >Cu 
(0.13±0.003) while that for D.modiglanin were Cd (0.06±0.002) = Cu (0.06±0.44). Cr, 
Ni and V were not detected in both species  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
95 
 
 
200 0.6
80 0.3
180
0.5
70 160
0.25
60 140
0.4
0.2 120
50
100 0.3
40 0.15 Density
Density
80 Mean conc
Mean conc
30 0.2
0.1 60
20 40
0.1
0.05
10 20
0 0 0 0
 
1.2 0.3 6 0.6
1 0.25 5 0.5
0.8 0.2 4 0.4
0.6 0.15 Density 3 0.3 Density
Mean conc
0.4 0.1 2 0.2 Mean conc
0.2 0.05 1 0.1
0 0 0 0
      
Fig. 4.7  Comparison of soil chromium concentrations and population densities of L. violaceous and D.modigliani (epicenter and 500m away from spill) 
96 
 
Density of L. violaceous
Density of D. modigliani
2
(earthworm/m2) (earthworm/m )
Jun'07
Aug
Oct
Dec
Feb
Apr
jun'08
Aug
Oct
Dec
Feb
Apr
Conc of chromium in epicenter
(mg/kg)
Concentration of chromium
Within epicenter
(mg/kg)
Density of L. violageous
(earthworm/m2)
Density of D.modigliani
(earthworm/m2)
Conc of chromium 500m away from spill
(mg/kg) Concentration of chromium 500m away from spil
(mg/kg)
 
 
200 0.25
80 0.2 180
0.18 160 0.2
70
0.16 140
60
0.14 120 0.15
50
0.12
100
Density
40 0.1
Density 80 0.1 Mean conc
0.08 Mean conc
30
60
0.06
20 40 0.05
0.04
10 20
0.02
0 0 0 0
 
1.2 0.2
6 0.25
0.18
1 0.16 5 0.2
0.8 0.14 4
0.12 0.15
0.6 0.1 3 Density
0.08 Density 0.1
0.4 2 Mean conc0.06 Mean conc
0.2 0.04 1 0.05
0.02
0 0 0 0
 
Fig. 4.8  Comparison of soil cadmium concentrations and population densities of L. violaceous and D. modigliani (epicenter and 500m away from spill) 
 
97 
 
Density of L. violaceous
Density of D. modigliani (earthworm/m2)
(earthworm/m2)
Conc of cadmium within epicenter 
(mg/kg)
Conc of cadmium in epicenter
(mg/kg)
Density of L. violaceous
(earthworm/m2)
Density of D. modigliani
(earthworm/m2)
Conc of cadmium 500m away from spill Conc of cadmium 500m away from spill (mg/kg)
(mg/kg)
 
200 10
180 9
80 10
160 8
9
70
140 7
8
60 120 6
7
50
6 100 5
Density
40 5 80 4 Mean conc
Density
4 Mean conc
30 60 3
3
20 40 2
2
20 1
10
1
0 0
0 0
 
6 10
1.2 10
9
9 5
1 88
7 4
7
0.8 6
6
0.6 5 3 5
4 Density 4 Density
0.4 23 Mean conc 3 Mean conc
2
0.2 2 1
1 1
0 0 0 0
          
Fig. 4.9   Comparison of soil zinc concentrations and population densities of L. violaceous and D. modigliani (epicenter and 500m away from spill) 
98 
 
Density of L. violaceous
Density of D. modigliani (earthworm/m2)
(earthworm/m2)
Conc of zinc within epicenter Conc of zinc within epicenter       (mg/kg)
(mg/kg)
Density of L..violaceous
(earthworm/m2)
Density of D. modiglianin
(earthworm/m2)
Conc of zinc 500m away  (mg/kg)
Conc of zinc 500m away (mg/kg)
 
80 0.3
70
0.25
200 0.3
60
180
0.2 0.25
50 160
140
0.2
40 0.15
Density 120
Mean conc
30 100 0.15
Density
0.1
80 Mean conc
20 0.1
60
0.05
10 40 0.05
20
0 0
0 0
 
200 0.3
180 6 0.3
0.25
160 5 0.25
140
0.2 4 0.2
120
3 0.15 Density
100 0.15
Density Mean conc
80 Mean conc 2 0.1
0.1
60 1 0.05
40
0.05 0 0
20
0 0
 
 
Fig. 4.10    Comparisons of soil lead concentrations and population densities of L. violaceous and D. modigliani (epicenter and 500m away from spill) 
99 
 
Density of L. violaceous Density of L. violaceous
(earthworm/m2) (earthworm/m2)
Conc of lead 500m away  (mg/kg) Concentration of lead within epicenter     (mg/kg)
Density of L. violaceous
Density of L. modigliani
(earthworm/m2)
(earthworm/m2)
Conc of lead 500m away  (mg/kg)
Conc of lead 500m away (mg/kg)
 
 
 
80 25 200 25
180
70
20 160 20
60
140
50
15 120 15
40 100
Density Density
10 Mean conc 80 10 Mean conc
30
60
20
5 40 5
10
20
0 0 0 0
   
  
1.2 25
1 6 25
20
5
0.8 20
15 4
15
0.6
Density 3
10 Mean conc 10 Density
0.4 2 Mean conc
5 5
0.2 1
0 0
0 0
  
Fig. 4.11   Comparison of soil manganese concentrations and population densities of L. violaceous and D. modigliani (epicenter and 500m away from 
spill) 
100 
 
Density of L. violaceous
(earthworm/m2) 
Density of D. modiglanin
(earthworm/m2) 
Conc of manganese within epicenter (mg/kg)
Conc of manganese within epicenter
(mg/kg)
Density of L. violaceous
(earthworm/m2) 
Density of D. modigliani
(earthworm/m2) 
Conc of manganese 500m away
(mg/kg)
Conc of manganese 500m away (mg/kg)
 
80 12 200 12
70 180
10 10
160
60
140
8 8
50
120
40 6 100 6
Density
30 Mean conc 80 Density
4 4
60 Mean conc
20
2 40
10 2
20
0 0
0 0
 
6 12
1.2 12
1 10 5 10
0.8 8 4 8
0.6 6 Density 3 6
0.4 4 Mean conc Density
2 4
Mean conc
0.2 2
1 2
0 0
0 0
    
 
Fig. 4. 12   Comparison of soil copper concentrations and population densities of L. violaceous and D. modigliani (epicenter and 500m away from spill) 
101 
 
Density of L. violaceous
Density of D. modigliani
(earthworm/m2) (earthworm/m2) 
Jun'07
Aug
Oct
Dec
Feb
Apr
jun'08
Aug
Oct
Dec
Feb
Apr
Conc of copper within epicenter
(mg/kg)
Conc of copper within epicenter(mg/kg)
Density of D. modigliani
(earthworm/m2) Density of L. violaceous
(earthworm/m2) 
Conc of copper 500m (mg/kg)
Conc of copper 500m away (mg/kg)
 
70 8 200 9
180
7 8
60
160
7
6
50 140
6
5
120
40 5
Density
4 100
Mean conc 4 Density
30
80
3 Mean conc
3
20 60
2
2
40
10 1
20 1
0 0 0 0
1.2 9 6 9
8 8
1 5
7 7
0.8 6 4 6
Density 5 Density5
0.6 3
Mean conc 4 Mean conc4
0.4 3 2 3
2 2
0.2 1
1 1
0 0 0 0
 
Fig. 4.13   Comparison of soil nickel concentrations and population densities of L. violaceous and D. modigliani (epicenter and 500m away from spill) 
102 
 
Density of L. violaceous
Density of D. modigliani (earthworm/m2)
(earthworm/m2)
Conc of nickel within epicenter Conc of nickel within epicenter   (mg/kg)
(mg/kg)
Density of L. violaceous
(earthworm/m2)
Density of D. modigliani
(earthworm/m2)
Conc of nickel 500m away   (mg/kg)
Conc of nickel 500m away
(mg/kg)
 
200 0.7
180
80 0.7 0.6
160
70 0.6
140 0.5
60
0.5 120
0.4
50
0.4 100 Density
40 0.3Density 80 Mean conc
0.3
30 Mean conc 60 0.2
0.2
20 40
0.1
10 0.1 20
0 0
0 0
 
80 0.7
70 0.6 6 0.7
60 5 0.6
0.5
0.5
50 4
0.4 0.4
40 3
Density 0.3
0.3 Density
Mean conc
30 2 0.2 Mean conc
0.2
20 1 0.1
0 0
10 0.1
0 0
 
Fig. 4. 14  Comparison of soil vanadium concentrations and population densities of L. violaceous and D. modigliani (epicenter and 500m away from 
spill) 
103 
 
Density of D. modiglanin Density of L. violaceous
(earthworm/m2) (earthworm/m2)
Jun'07 Jun'07
Aug Aug
Oct Oct
Dec Dec
Feb Feb
Apr Apr
jun'08 jun'08
Aug Aug
Oct Oct
Dec Dec
Feb Feb
Apr Apr
Conc of vanadium within epicenter Conc of vanadium within epicenter
(mg/kg) (mg/kg)
Density of L. violaceous
Density of earthworm (earthworm/m2)
(earthworm/m2)
Jun'07
Aug
Oct
Dec
Feb
Apr
jun'08
Aug
Oct
Dec
Feb
Apr
Conc of vanadium 500m away Concn of vanadium 500m away  (mg/kg)
(mg/kg)
 
 
 
 
 
 
 
 
400
350
300
250
200
500m away
Epicenter
150
100
50
0
Time
 
 
Fig.4.15: Comparison of L.violaceous abundance in the epicentre of oil spill and 500m 
away from the spill 
  
 
 
 
104 
 
Number of earthworms
Jun'07
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr'09
 
 
25
20
15
500m away
10
Epicenter
5
0
Time
 
 Fig.4.16: Comparison of D. modigliani abundance in the epicentre of oil spill and 500m 
away from the spill. 
 
 
 
 
 
105 
 
Number of earthworms
Jun'07
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr'09
 
30
25
20
15
500m away
Epicenter
10
5
0
Time
 
Fig.4.17  Comparison of E.afroccidentalis abundance in the epicentre of oil spill and 500m 
away from the spill.  
  
          
 
 
 
 
       
 
 
 
 
106 
 
Number of earthworms
Jun'07
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr'09
 
12
10
8
6
500m away
Epicenter
4
2
0
Time
 
 
Fig.4.18: Comparison of H.lagosensis abundance the epicentre of oil spill and 500m away 
from the spill 
 
 
 
 
107 
 
Number of earthworms
Jun'07
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr'09
 
 
Table 4. 15: Heavy metal accumulation in L.violaceous and D.modiglani species 
 
Metals Epicenter 500m away 
measured in Metal Conc (mg/g) (Mean±SD)  Metal Conc (mg/g) (Mean±SD) 
earthworm   
spp 
Mn1 ND ND 
Mn2 3.66±0.04 1.37±0.06 
Cu1 ND ND 
Cu2 0.13±0.003 0.09±0.02 
Zn1 6.7±0.4 3.76±1.06 
Zn2 5.46±0.03 2.03±0.8 
Pb1 ND ND 
Pb2 ND ND 
Cd1 0.06±0.002 0.05±0.02 
Cd2 0.17±0.003 0.06±0.02 
Cr1 ND ND 
Cr2 ND ND 
Ni1 ND ND 
Ni2 ND ND 
V1 ND ND 
V2 ND ND 
1 = D.modigliani 
2= L.violaceous  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
108 
 
 
 
4. 7 Correlation of physicochemical parameters with earthworm abundance 
The statistical correlation of earthworm abundance in the epicenter and 500m 
away were done with (i) heavy metal concentration which includes Chromium (Cr), 
Cadmium (Cd), Magnese (Mn), Nickel (Ni), Lead (Pd), Zinc (Zn) and Vanadium (V) 
and Other parameters including Sulphate (SO4), Nitrate (NO3), pH level, temperature, 
Total organic carbon (TOC) and Total organic matter (TOM) (Table 4.16 and 4.17) 
and (iii) climatic parameters like rainfall (RF) and soil temperature (ST)  (Fig.4.19 and 
4.20). 
Within the epicenter, concentration of zinc in soil alone showed a strong positive 
colleration with the abundance of both earthworm species encountered, (0.77 and 0.65 
for D.modiglanin and L.violaceous respectively) while concentrations of chromium, 
cadmium,  copper and nickel showed weak negative correlation (-0.31, -0.45, -0.23 
and -0.1 ) with L.violaceous species. Also, pH and concentration of Total Petroleum 
Hydrocarbon (TPH) showed weak negative correlation with both earthworm species 
while concentrations of nitrate (NO3), Total Organic Carbon (TOC) and Total Organic 
Matter (TOM) showed a strong positive correlation with both earthworm species 
(Table 4.16). The concentrations of chromium and cadmium 500m away from the 
spill, showed weak negative correlation with the abundance of individual earthworm 
species encountered, also the concentration of nickel showed a weak negative 
correlation with the abundance of E.afroccidentalis and H.lagosensis alone. The 
concentration of zinc showed positive correlation with E.afroccidentalis and 
H.lagosensis and not D.modiglanin and L.violaceous (Table 4.17) 
Soil temperature had a negative correlation with all earthworm species whereas 
rainfall and soil moisture had positive correlations with earthworm abundance within 
the epicenter and 500m away from spill. (Fig 4.19 and Fig 4.20). 
 
 
 
 
 
 
109 
 
 
 
REPLACE WITH CORRELATION 
Table 4.16: Correlation of earthworm species with heavy metal concentrations and other                   
parameters within the epicenter of oil spill 
 
Earthworm Cr Cd Pb Zn Cu Mn Ni V 
species 
D.modiglanin 0.003 -0.29 0.04 0.77 0.10 0.35 0.09 0.09 
L.violaceous -0.31 -0.45 0.17 0.65 -0.23 0.24 -0.1 0.28 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
110 
 
 
 
 
Table 4.17: Correlation of earthworm species with heavy metal concentrations and other                   
parameters 500m away from oil spill 
 
Earthworm SO4 NO3 PO4 PH K Na Ca TOC TOM TPH 
species 
D.modiglanin 0.38 0.55 0.43 -0.09 0.48 0.76 0.56 0.67 0.67 -0.25 
L.violaceous 0.51 0.66 0.41 -0.27 0.36 0.78 0.35 0.75 0.75 -0.31 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
111 
 
 
 
 
0.8
0.6
0.4
0.2
(RF)
0
(ST)
L.v D.m H.l E.a All  Spp
(SM)
-0.2
-0.4
-0.6
-0.8
Earthworm Spp
 
Fig 4.19: Correlation of climatic parameters with earthworm species abundance within the 
epicenter of oil spill 
Key: 
L.v  =  L. violaceous 
D.m = D. modiglianin 
H.l = H. lagosiensis 
E.a = E. afroccidentalis 
RF= Rainfall 
ST= Soil temoerature 
SM= Soil moisture 
 
 
 
 
112 
 
correlation
 
 
 
1
0.8
0.6
0.4
0.2
(RF)
0
(ST)
L.v D.m H.l E.a All  Spp
(SM)
-0.2
-0.4
-0.6
-0.8
-1
Earthworm Spp
 
 
Fig. 4.20: Correlation of climatic parameters with earthworm species abundance 500m 
away from oil spill 
 
Key: 
L.v  =  L. violaceous 
D.m = D. modiglianin 
H.l = H. lagosiensis 
E.a = E. afroccidentalis 
RF= Rainfall 
ST= Soil temoerature 
SM= Soil moisture 
 
 
 
 
 
 
 
113 
 
correlation
 
4.8 Earthworm toxicity tests 
The result indicated that both earthworm species showed low percentage survival 
(20% and 10% for L.violaceous and D.modiglanin respectively) compared to that in 
the control soil. However, in the subsequent year, L.violaceous showed a higher 
percentage survival of 70% compared to D.modiglanin which showed a lower 
percentage survival of 30% (Table 4.18).  
The result of avoidance test indicated that there was high percentage migration of both 
earthworm species into the control soil whereas, by the subsequent year, there was 
lower percentage migration of L.violaceous species but not D.modiglanin into the 
control soil (Table 4.19). 
 4.9 Ex-situ bioremediation study 
During the ex-situ bioremediation study, TPH and Heavy metal concentrations 
were monitored and the mean concentrations and t-test results for various soil types 
against control (non- contaminated soil) are shown in Table 4.20 – 4.27. T-test results 
indicated a significant reduction of the concentrations of TPH and all heavy metals 
except copper in the earthworm treated soil (CSE) during the period of study (P>0.05) 
unlike the t-test results of other soil type (CS) which showed no significant reduction 
(P<0.05). 
 
 
 
 
 
 
 
 
 
114 
 
 
 
 
      Table 4.18: Percentage means of surviving earthworm species   
Earthworm Oct, 2008 Oct, 2009
species
CSE NSE CSE NSE
(%) (%) (%) (%)
L.violaceous 20 90 70 80
D.modiglanin 10 70 30 90
CSE = Contaminated soil and earthworm
NSE = Non-contaminated soil and earthworm
 
 
 
 
 
 
 
 
 
 
115 
 
 
          Table 4.19 Percentage means of migrated earthworm species 
Earthworm Oct, 2008 Oct, 2009
species
CSE NSE CSE NSE
(%) (%) (%) (%)
L.violaceous 30 70 60 40
D.modiglanin 0 100 20 80
CSE = Contaminated soil and earthworm
NSE = Non-contaminated soil and earthworm
 
 
 
 
 
 
 
 
 
116 
 
 
         Table 4.20: Mean concentrations of Total Hydrocarbon in soil samples for   
bioremediation study 
 
NS CS CSE
(ex-situ) (ex-situ) (ex-situ) 
Pre-treatment 0.41 2.65 2.37
6 weeks 0.39 2.35 1
12 weeks 0.4 2.3 0.85
*P-value - 0.0013 0.0851
Sign. - P<0.05 P>0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS=Non-contaminated   
soil (Control), CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
 
 
 
117 
 
 
Table 4.21: Mean concentrations of Copper in soil samples for bioremediation study 
 
NS CS CSE
(ex-situ) (ex-situ) (ex-situ) 
Pre-treatment 0.32 0.77 0.76
6 weeks 0.3 0.72 0.63
12 weeks 0.31 0.67 0.59
*P-value 0.0020 0.0088
Sign. P<0.05 P<0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS= Non-contaminated  soil (Control)  
CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
 
 
 
118 
 
 
Table 4.22: Mean concentrations of Lead in soil samples for bioremediation study 
 
NS CS CSE
(ex-situ) (ex-situ) (ex-situ) 
Pre-treatment 0.08 0.17 0.16
6 weeks 0.07 0.16 0.09
12 weeks 0.06 0.16 0.06
*P-value 0.0006 0.1499
Sign. P<0.05 P>0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS= Non-contaminated  soil (Control)  
CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
 
 
 
 
119 
 
 
             
           Table 4.23: Mean concentrations of Vanadium in soil for bioremediation study 
 
NS CS CSE
(ex -situ) (ex-situ) (ex-situ) 
Pre-treatment 0.18 0.59 0.57
6 weeks 0.13 0.57 0.5
12 weeks 0.16 0.43 0
*P-value 0.0095 0.1911
Sign. P<0.05 P>0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS= Non-contaminated  soil (Control)  
CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
120 
 
 
 
 
            Table 4.24: Mean concentration of zinc in soil samples for bioremediation study 
 
NS CS CSE
(ex-situ) (ex-situ) (ex-situ) 
Pre-treatment 0.26 0.42 0.46
6 weeks 0.21 0.51 0.35
12 weeks 0.29 0.47 0.11
*P-value 0.019 0.3477
Sign. P<0.05 P>0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS= Non-contaminated  soil (Control)  
CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
 
 
121 
 
 
 
 
 
Table 4.25: Mean concentrations of manganese in soil samples for bioremediation 
study 
 
NS CS CSE
(ex-situ) (ex-situ) (ex-situ) 
Pre-treatment 1.82 8.38 8.54
6 weeks 1.93 6.62 4.81
12 weeks 1.63 0.47 0
*P-value 0.1424 0.1928
Sign. P<0.05 P>0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS= Non-contaminated  soil (Control)  
CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
122 
 
 
 
Table 4.26: Mean concentrations of Cadmium in soil samples for bioremediation study 
 
NS CS CSE
(ex-situ) (ex-situ) (ex-situ) 
Pre-treatment 0 0.02 0.02
6 weeks 0 0.03 0
12 weeks 0 0.01 0
*P-value 0.0370 0.2113
Sign. P<0.05 P>0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS= Non-contaminated  soil (Control)  
CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
 
 
 
 
 
123 
 
 
 
Table 4.27: Mean concentrations of Chromium in soil samples for bioremediation 
study 
NS CS CSE 
Pre-treatment 0 0.08 0.08
6 weeks 0 0.06 0.02
12 weeks 0 0.07 0
*P-value 0.0033 0.1499
Sign. P<0.05 P>0.05
*t-test (P-value) on concentrations of other soil types against control soil
Key: CS = Contaminated Soil, NS= Non-contaminated  soil (Control)  
CSE=Contaminated Soil with earthworm
 
 
 
 
 
 
 
 
 
 
 
124 
 
 
 
                                                       CHAPTER FIVE 
  5.0                                                   DISCUSSION 
              5.1 Water quality analysis 
 
This study shows that mean concentrations of Lead (Pb) in most water sampled and 
analysed during the study period were above the WHO and NESREA drinking water 
limit of 0.01mg/L and 0.2mg/L respectively. The elevated concentration might be due 
to the inferno which produced fumes with deposits seeping into the ground water. In 
addition, earlier investigations show that much of the gasoline available in developing 
countries are still heavily leaded (Borasin et al., 2002).  The school borehole water 
(GW5) had one of the highest concentrations of Lead (0.15mg/l in August, 2007) and it 
is a major source of water for drinking by the school community, however this dried up 
during the course of the study. The elevated concentration of Lead (Pb) in borehole 
water could have arisen from metal plumbing systems containing Lead in pipes, solder, 
fittings or the service connections as reported by WHO and EPA (WHO 1993; WHO 
2003. A likely consequence of high Lead level is bioaccumulation which could 
eventually result in Lead poisoning of the populace.  
A decrease of IQ in children is reported to be associated with an increase in blood 
Lead (>30mg/L) and tooth Lead. It is also reported that prenatal exposure to Lead may 
have early effects on mental development that do not persist after the age of 4 years 
(Schwartz, 1994, McMichael et al., 1994). Other possible consequences may include 
fatigue, insomnia, retarded development of foetus, hearing and vision impairment and 
decreased sperm count. A case of a deafened student was reported during this study; 
although there was no study to prove that the cause of the deafening was Lead 
poisoning.  
The mean cadmium concentrations were higher than the WHO and NESREA 
drinking water limit of 0.003mg/l for all the well water samples analysed with highest 
value of 0.1mg/L recorded in the month of April, 2008. The values later dropped 
below these standards and then fluctuated between 0.001mg/L and 0.006mg/L from 
June, 2008 to April, 2009. The relatively high concentration of cadmium in water 
could generally be due to other natural contaminations like weathering, forest fires and 
volcano; in this case, the inferno could have contributed to the high levels of 
125 
 
 
cadmium. Cadmium is known to cause high blood pressure, liver disease and brain 
damage (ATSDR, 1999) 
Nickel (Ni) concentrations were higher than WHO drinking water limit of 
0.02mg/L in all the water samples investigated. The highest concentration of Nickel 
(Ni), 2.85mg/L in December, 2008 was obtained in the surface water samples (SW1). 
This is indicative of hydrocarbon contamination due to the oil spill. Nickel is a 
micronutrient but an excessive level of the metal in the soil might be toxic to some soil 
fauna, like earthworms, which are adjuncts to the micro-flora in organic matter 
decomposition and may also reduce heterotrophic activity of the micro-flora (Osuji, 
2002). The increase in Nickel level recorded in water  samples (GW and SW) 
especially in the second year is not fully understood, however, it could be somewhat 
connected with the enormous Ijegun (adjacent settlement, about 1 km away) oil spill 
which occurred at this period.  
Zinc (Zn), copper (Cu) and manganese (Mn) concentrations were all within WHO 
drinking water limits of 3.00mg/l, 1.00mg/l and 0.4mg/l respectively for all the water 
sampled within the two years of investigation. The highest levels of Zinc (Zn), copper 
(Cu) and Manganese (Mn) obtained were 2.65mg/l (GW1, December 2008), 0.67mg/l 
(GW2, February 2009) and 0.35mg/l (GW6 April 2008) respectively. 
 
Petrol has a high penetrating ability due to its very low boiling point and volatility 
even at room temperature than the higher boiling point of oils like diesel. However, 
the latter has more chronic effect and persists longer in the environment causing 
harmful effects than light oils which may be evaporated before fatal damages are 
caused. From results obtained, especially close to the point of spills, it is revealed that 
the %TOC and %TOM of soil samples were relatively low as compared with those 
sampled away from the point of spills. Some heavy metal loads observed in soils from 
this study could be attributed to the low soil pH. According to Emongor (2007), low 
pH 5.5-5.9, is the optimal range within which heavy metals catalyse. Organic-Pb will 
form complexes and become more soluble and bioavailable in the soil. Chromium in 
some forms may be cationic and therefore adsorb onto clay particles, organic matter, 
metal hydroxide, and other negatively charged particles or adsorb to oxide and clay 
particles. Compared to water medium, the concentration of Cr ions in soil solution 
126 
 
 
may have been lower given the soil solution is a heterogenous mixture of ions which 
may interfere with the availability and uptake of Cr ions (Sivakumar and Subbhuraam, 
2005). Metals like chromium may pose public health risks such as dermatitis 
especially when in direct contact with the skin while Zinc and Nickel are known to 
replace enzyme polymerase in DNA formation thereby leading to mutation.  
Total petroleum hydrocarbon (TPH) ranged from 0.05mg/kg to 6.32mg/kg in soil 
providing evidence of hydrocarbon contamination at the study site. Usually, such 
hydrocarbon ranges deplete available oxygen and reduce gaseous diffusion in surface 
and subsurface soils, thereby stressing the organisms trapped beneath, some of which 
eventually die of asphyxiation. Such hydrocarbon levels may also discourage plant 
growth, thereby reducing the population density and species diversity of plant cover 
and other vegetations found in the affected area. The fire incidence that followed the 
spills had consumed a major amount of petroleum hydrocarbon at the point of spill, 
hence the relatively low value of petroleum hydrocarbon. The results obtained 
especially at the point of spills presuppose that there are still contaminable percolates 
of the spilled-oil at depths of the polluted site sampled. In soils, petroleum 
hydrocarbon creates conditions which lead to availability of heavy metals toxic to 
plants and the soil remains unsuitable until the crude oil is degraded to a tolerable 
level. 
The fumes from the resultant inferno contain complex mixture of very toxic gases 
like toluene which is known to synergistically act with acetaminophens causing 
negative impact on the central nervous system (Irwin, 1997; Zhen et al., 1994). This 
also, could have been the cause the deafening of a school girl; however, the claim was 
not investigated by this study. 
  5.2 Earthworm abundance, distribution and densities 
The low diversity of earthworm species is an indication of the impact of the spill 
on fauna in Agaye soil. The species E. afroccidentalis and H. lagosensis, were most 
impacted by the spill as they were only encountered in the second year and the area 
500m away from the spill. The soil within 100m of the spill was the most affected 
from the spill and inferno as there was low abundance of earthworm species and there 
was a significant difference between the abundance of earthworm species during the 
127 
 
 
period immediately after the spill but a marked improvement by the second year. Osuji 
and Adesanya (2005) had reported the impact of hydrocarbon contaminant on 
nematode and earthworms.  
The marked recovery of the earthworm population size and increased diversity of 
earthworm species observed in the soil by the second year of the study could be 
attributed to natural attenuation and enhanced activities of the earthworms. Earthworm 
species have been shown to improve remediation of petroleum contaminated soils 
(Zachery and Reid, 2008a; Nana – Osei Mainoo et al, 2008). The improvement of soil 
structure and texture being enhanced by earthworm is reported to be factors 
contributing to increasing microbial load and action. 
Greatest percentage of earthworm biomass was contributed by L.violaceous, 
followed by D.modiglanin. This investigation showed that biomasses of H.lagosensis 
and E. afroccidentalis were insignificant to the total biomass of earthworms. The 
species L.violaceous was identified to be the most abundant earthworm spp found 
within Agaye community, this earthworm species showed tolerance to the spill as 
indicated by its occurrence throughout the period of study. This also confirms the 
report of Segun and Owa (2003) that L.violaceous is commonly found in south 
western Nigeria.  
    5.3 Effect of physicochemical / climatic parameters on earthworm abundance 
Although there is information on the general distribution pattern of earthworms in 
the SW zone of Nigeria as reported by Owa and Olojo, 2003; Segun and Owa (2003), 
there is limited information on the influence of oil spills on earthworm distribution 
patterns.  
The earthworms were more abundant during the raining seasons because certain 
physiological activities of earthworms such as cutaneous respiration and excretion of 
nitrogenous ammonia and urea need moist environment. This in turn, is essential for 
the maintenance of their life processes (Kale and Karmegam, 2010) hence; there was a 
relative increase in abundance during the rainy season with higher moisture content.  
Soil moisture plays a major role in earthworm abundance and diversity as 
observed by Edwards and Bohlen, 1996 ; Nana – Osei and Mainoo et al., (2008). 
Earthworms are sometimes more abundant in areas with higher soil organic carbon 
128 
 
 
content as reported by Hendrix et al., (1992),  Poier and Richter (1992); Nuutinen et 
al., (2001). Whalen, 2004 and Rossi et al. (2006) however disagreed with this view. 
The climatic parameters, (soil temperature, soil moisture and rainfall) showed seasonal 
fluctuations and earthworm abundance and biomass throughout the year. Earthworm 
activity and populations are determined essentially by the moisture content of the soil 
as observed in this study.  
Water constitutes 75–90 percent of the body weight of earthworms. So the prevention 
of water loss is a major factor for their survival. They apparently lack a mechanism to 
maintain constant internal water content, so that their water content is influenced 
greatly by the water potential of the soil, which directly depends on the adequate 
availability of soil moisture. The temperature and moisture are usually inversely 
related and higher surface temperature and dry soils are limiting factors to earthworms 
than low surface temperature and water logged soils.  
Soil temperatures also play an important role in the maintenance of earthworm 
population in an ecosystem and available information from this study also indicates 
the negative correlation of soil temperature to earthworm population. According to 
Radha and Ntachimuthu, (2010); temperature also largely affects activity of 
earthworms in temperate regions. However, tropical species are known to tolerate 
O
higher temperatures to an extent (max 30 C); this could be because in tropical regions 
the temperature fluctuations are minimal when compared to temperate regions. 
   5.4 Correlation between some physicochemical parameters and earthworm abundance 
In this present study only a lower percentage of the earthworm population 
fluctuations can be explained by the physicochemical effect and higher percentage by 
climatic parameters. It is presumed that the remaining may depend on other 
environmental factors. The correlation analysis technique may be used to quantify and 
rationalize the effects of physicochemical parameters on the earthworm population. 
However, no single factor is likely to be solely responsible for the distribution of 
earthworms, but rather the interaction of several factors provides suitable soil 
conditions for the existence of earthworm populations. Radha and Ntachimuthu (2010) 
129 
 
 
also reported a similar trend in their review on Indian indigenous earthworm 
distribution pattern. 
The results from this investigation indicates a negative impact of the spill on the 
earthworm community and since earthworms play a vital role in maintaining the soil 
structure and texture, the impact of this spill may have affected the fertility and 
productivity for agricultural use. 
   5.5 Bioremediation  
This study showed the accumulation of some heavy metals by L. violaceous and D. 
modiglanin and also indicated a possible positive role of L.violaceous in remediating 
heavy metals (Cr, Cd, Pb, Zn, Ni and V) and TPH except copper in the soil. Similar 
research by Parra et al, (2010) revealed that with the use of Eisenia fetida, there was 
efficiency of remediating arsenic and mercury in approximately two weeks. They 
recommended that Eisenia fetida be used to process hazardous solid and liquid wastes 
with high metal content. Earthworms have been reported to stimulate the degradation 
of petroleum hydrocarbons in soil according to reviews reported by McCosh and 
Getliff (2004); Zachary and Reid (2008). Zachary and Reid (2008), Kale and 
Karmegam (2010) and Sinha, 2010 had also reported that earthworms play a role in 
remediation. The effectiveness of earthworms in remediation they reported owes to the 
fact that earthworms‟ digestion pattern (microflora of their gut enhances 
biodegradation), turbation and borrowing activities have been shown to improve 
conditions suitable for microbial action thereby enhancing biodegradation.  Also they 
absorb metals thereby bioaccumilating them into their tissues. Furthermore, Kreis et 
al., (1987) and Vandecasteele, et al., (2004) reported the transfer of pollutants towards 
other higher trophic levels, Earthworms constitute the largest terrestrial faunal biomass 
and they occupy a key position.  
 
 
 
130 
 
 
                                                    CHAPTER SIX 
6.0                                               CONCLUSION 
 
This study recorded high levels of lead, cadmium and chromium found in the 
water and soil of the study area. The earthworm species, L.violaceous was the most 
tolerant earthworm species to petroleum pollution than other indigenous earthworm 
species found in the study site. The study also showed that L.violaceous was effective 
in remediating heavy metal in the soil. The recovery of a petroleum polluted site was 
successful monitored with the use of tropical earthworms as bioindicator and the 
results of physicochemical analysis and earthworm ecology provide a data base for 
further research of the study area. 
One serious environmental problem the spillage caused is the leakage of oil into 
the ground water. The extent of the penetration of spill was inadequately estimated as 
only one borehole existed during the period of study, all wells sampled in all the 
houses were shallow. It is therefore necessary to monitor more ground water 
(boreholes) for oil and heavy metal contents. This investigation has also shown the 
study area have high level of TPH. There was significant difference in the measured 
concentration of TPH between the years of study. 
There are many oil spill sites and several loss of number and diversity of fauna 
and flora in ecosystems. There is need to develop cheaper remediation techniques 
especially for third world countries like Nigeria where oil spills are common placed 
and response by government or oil companies are quite slow. Since the earthworm 
species, L.violaceous have shown potentials in remediation of oil contaminants, more 
research can be done to ascertain its efficacy, its breeding and culturing and exploiting 
its use as a bioremediant.  
Scientists are therefore saddled with the responsibility to search for solutions 
that address oil independence and security, protect the global environment and 
stimulate global economy. Although, new technologies to improve energy efficiency 
and generate energy and minimizing pollution are being researched, use of fossil fuel 
could be significantly decreased if advanced vehicle technologies, such as electric-
hybrid and hydrogen-fuel cells, are widely deployed. Renewable energy resources, 
such as biomass, geothermal, solar, tidal and wind, are already abundant and located 
131 
 
 
throughout the United States. In Nigeria, distributed generation of renewable energy 
sources is a way to diversify energy supply hence disbursing the locations of energy 
generation. Interdisciplinary approach of environmental problem-solving through 
combination of disciplines like biotechnology, microbiology, genetic engineering on 
the sphere of ecological practices has given rise to promising research and application 
of bioremediation tools.  
Generally, Oil companies should be mandated to play parts in working with 
N.N.PC on remedial intervention in order to achieve the target values in oil spilled 
areas like Agaye community. It is also necessary to develop modified oil pipelines with 
components which will make them more difficult to tamper with. N.NP.C should foster 
the cooperation of indigenes, local and federal governments in the protection of oil 
installations. It is specifically recommended that the populace in Agaye community be 
educated on the dangers of using their well water and other water sources for domestic 
purposes. Government should construct standard and deep bore hole water supply as an 
alternative water source for the populace. N.N.P.C should replace obsolete pipes and 
town planners should ensure that construction of buildings should be as far as the 
stipulated perimeter distance from petroleum pipelines.  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
132 
 
 
 
 
 
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   Zhendi, W.  (2003):  Fate and Identification of Spilled Oils and Petroleum 
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  Zachery, H.A. and Reid, B.J. (2008a): The co-application of earthworms 
(Dendrobaena veneta) and compost to increase hydrocarbon losses from diesel 
contaminated soils”. Soil Biology and Biochemistry, 40.2970-2976.  
 
  Zachary, A. H. and Reid B.J.  (2008b):  Earthworm assisted bioremediation of 
organic contaminants. Environment International. 34.1072-1081 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
150 
 
 
APPENDICES 
I: HEAVY METALS CONCENTRATION OF WATER SOURCES IN IJE-ODODO 
Heavy metal concentration for water samples, June 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.07 0.03 0.03 0.52 0.19 0.20 0.30 0.20 
W2 0.04 0.02 0.02 0.61 0.18 0.21 0.10 0.15 
W3 0.09 0.05 0.05 0.73 0.21 0.15 0.12 0.10 
W4 0.10 0.03 0.02 0.69 0.15 0.19 0.09 0.09 
Rv 0.02 0.03 0.03 0.36 0.10 0.12 1.95 0.25 
Rv1 0.01 0.04 0.02 0.43 0.14 0.13 2.05 0.20 
Tsch 0.02 0.03 0.02 0.26 0.15 0.13 0.10 0.20 
Wsch 0.06 0.05 0.06 0.60 0.20 0.15 0.25 0.15 
 
 
Heavy metal concentration for water samples, Aug 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.06 0.03 0.03 0.50 0.22 0.21 0.35 0.21 
W2 0.04 0.04 0.02 0.60 0.20 0.22 0.20 0.20 
W3 0.08 0.06 0.06 0.60 0.30 0.10 0.22 0.20 
W4 0.09 0.03 0.02 0.60 0.20 0.20 0.08 0.08 
Rv 0.04 0.03 0.04 0.26 0.12 0.15 2.00 0.21 
Rv1 0.01 0.05 0.03 0.52 0.15 0.15 2.10 0.30 
Tsch 0.02 0.03 0.15 0.05 0.20 0.40 0.15 0.15 
Wsch 0.05 0.07 0.05 0.50 0.01 0.15 0.30 0.20 
 
 
Heavy metal concentration for water samples, Oct 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.03 0.06 0.05 0.47 0.12 0.15 0.20 0.18 
W2 0.02 0.01 0.03 0.31 0.13 0.17 0.10 0.14 
W3 0.06 0.02 0.07 0.36 0.15 0.13 0.10 0.10 
W4 0.05 0.03 0.01 0.52 0.20 0.17 0.05 0.07 
Rv 0.01 0.03 0.03 0.39 0.10 0.10 1.80 0.28 
Rv1 0.05 0.06 0.02 0.37 0.09 0.05 2.01 0.30 
Tsch 0.03 0.05 0.02 0.19 0.10 0.06 0.13 0.15 
Wsch 0.09 0.04 0.03 0.43 0.15 0.21 0.28 0.15 
Heavy metal concentration for water samples, Dec 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.03 0.02 0.02 0.27 0.04 0.06 0.19 0.10 
W2 0.04 0.01 0.01 0.25 0.09 0.10 0.12 0.12 
W3 0.04 0.03 0.02 0.30 0.05 0.07 0.15 0.09 
W4 0.03 0.06 0.05 0.19 0.08 0.06 0.01 0.02 
Rv 0.07 0.05 0.10 0.18 0.07 0.07 1.50 0.30 
Rv2 0.06 0.05 0.15 0.21 0.09 0.10 1.55 0.29 
Tsch 0.01 0.02 0.03 0.19 0.06 0.19 0.15 0.21 
Wsch 0.05 0.01 0.02 0.14 0.11 0.15 0.21 0.19 
 
Heavy metal concentration for water samples, Feb 2008 
151 
 
 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.03 0.05 0.05 0.30 0.07 0.06 0.20 0.20 
W2 0.04 0.02 0.03 0.27 0.10 0.05 0.15 0.18 
W3 0.06 0.05 0.03 0.25 0.05 0.05 0.18 0.10 
W4 0.05 0.07 0.06 0.01 0.09 0.06 0.01 0.04 
Wsch 0.06 0.04 0.02 0.20 0.07 0.18 0.28 0.20 
Rv 0.05 0.05 0.18 0.22 0.08 0.06 1.80 0.32 
         
 
Heavy metal concentration for water samples, April 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.08 0.12 0.05 0.67 0.27 0.31 0.50 0.16 
W2 0.09 0.13 0.07 0.72 0.25 0.3 0.40 0.01 
W3 0.17 0.1 0.08 0.6 0.21 0.29 0.55 0.19 
W4 0.07 0.1 0.11 0.59 0.24 0.35 0.15 0.09 
Wsch 0.09 0.1 0.05 0.45 0.19 0.19 0.30 0.15 
Rv 0.1 0.11 0.06 0.62 0.13 0.25 2.00 0.91 
         
 
Heavy metal concentration for water samples,  Jun 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.09 0.001 0.07 0.10 0.05 0.21 0.90 0.20 
W3 0.05 0.002 0.06 0.14 0.01 0.25 0.50 0.15 
W4 0.05 0.001 0.03 0.10 0.06 0.21 0.20 0.10 
Wsch 0.06 0.003 0.09 0.15 0.05 0.16 1.00 0.25 
Rv 0.05 0.001 0.07 0.12 0.07 0.22 2.50 0.20 
         
 
Heavy metal concentration for water samples, Aug 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.08 0.001 0.08 0.95 0.06 0.22 0.95 0.21 
W2 0.05 0.001 0.08 0.09 0.04 0.22 0.90 0.20 
W3 0.05 0.001 0.04 0.12 0.04 0.21 0.30 0.15 
W4 0.04 0.001 0.04 0.12 0.05 0.21 0.21 0.12 
Wsch 0.07 0.004 0.09 0.18 0.06 0.16 1.10 0.30 
Rv 0.05 0.002 0.08 0.10 0.07 0.24 2.53 0.21 
         
 
Heavy metal concentration for water samples, Oct 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.005 0.001 0.007 1.05 0.29 0.15 0.98 0.21 
W2 0.009 0.003 0.010 1.05 0.32 0.10 0.90 0.22 
W3 0.007 0.006 0.001 0.73 0.19 0.17 0.35 0.19 
W4 0.008 0.005 0.002 1.11 0.22 0.18 0.55 0.19 
Wsch 0.020 0.006 0.002 0.96 0.21 0.14 1.60 0.32 
Rv 0.007 0.002 0.005 2.60 0.53 0.19 2.70 0.22 
 
Heavy metal concentration for water samples, Dec 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.004 0.001 0.008 1.07 0.30 0.15 0.90 0.22 
W2 0.009 0.002 0.020 1.09 0.35 0.12 0.92 0.22 
152 
 
 
W3 0.008 0.002 0.002 0.83 0.20 0.25 0.36 0.23 
W4 0.007 0.003 0.002 1.15 0.23 0.20 0.58 0.21 
Wsch 0.030 0.004 0.003 0.99 0.24 0.16 1.59 0.35 
Rv 0.010 0.002 0.005 2.65 0.65 0.22 2.85 0.25 
         
 
Heavy metal concentration for water samples, Water Feb 2009 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.004 0.002 0.009 1.08 0.40 0.20 0.99 0.25 
W2 0.010 0.002 0.020 1.10 0.37 0.13 0.90 0.23 
W3 0.010 0.001 0.002 0.80 0.30 0.24 0.35 0.23 
W4 0.008 0.003 0.002 1.00 0.27 0.20 0.59 0.23 
Wsch 0.030 0.005 0.003 0.95 0.25 0.17 1.60 0.37 
Rv 0.030 0.004 0.007 2.60 0.67 0.24 2.80 0.28 
 
 
 
Heavy metal concentration for water samples, Apr 2009 
CODE Cr Cd Pd Zn Cu Mn Ni V 
W1 0.003 0.001 0.009 1.1 0.45 0.19 0.98 0.20 
W2 0.009 0.001 0.010 1.1 0.30 0.10 0.91 0.24 
W3 0.010 0.001 0.001 0.7 0.31 0.23 0.30 0.20 
W4 0.006 0.002 0.001 1.0 0.25 0.21 0.60 0.24 
Wsch 0.040 0.004 0.003 0.9 0.24 0.17 1.50 0.38 
Rv 0.040 0.003 0.005 2.5 0.65 0.14 2.70 0.30 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
153 
 
 
II: HEAVY METALS CONCENTRATION OF SOIL SAMPLES IN IJE-ODODO 
 
Soil Jun 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.21 0.15 0.14 2.91 1.99 5.99 2.14 0.10 
S2 0.20 0.12 0.12 3.01 5.26 13.05 1.20 0.18 
S3 0.19 0.10 0.12 1.96 3.29 12.01 0.50 0.12 
S4 0.17 0.09 0.15 1.21 4.01 10.21 0.10 0.18 
Sv2 0.23 0.17 0.13 1.83 2.01 14.02 4.05 0.15 
Ssch 0.19 0.07 0.10 1.01 2.32 3.30 0.45 0.12 
Sf 0.21 0.15 0.12 1.96 1.90 12.19 1.05 0.10 
Sv1 0.19 0.09 0.10 0.99 1.00 3.50 8.05 0.15 
Soil Aug 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.22 0.13 0.16 2.95 1.95 6.01 2.20 0.12 
S2 0.20 0.13 0.15 3.20 5.20 13.5 1.31 0.20 
S3 0.20 0.11 0.11 1.98 2.50 11.99 0.51 0.14 
Sv2 0.25 0.16 0.12 1.90 4.06 14.00 4.10 0.16 
S4 0.18 0.09 0.10 1.25 2.05 0.24 0.11 0.17 
Ssch 0.19 0.06 0.10 1.02 2.35 4.01 0.46 0.15 
Sf 0.22 0.16 0.10 1.99 2.01 12.50 1.10 0.12 
Sv1 0.19 0.10 0.15 0.98 1.09 3.51 8.00 0.16 
Soil Oct 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.15 0.12 0.09 1.46 1.21 3.21 1.05 0.12 
S2 0.19 0.10 0.10 2.71 4.20 9.95 1.00 0.16 
S3 0.32 0.06 0.17 1.71 3.00 10.99 0.55 0.19 
Sv2 0.15 0.11 0.09 1.28 2.99 10.16 3.05 0.22 
Sv1 0.10 0.07 0.10 1.39 1.76 5.96 8.00 0.20 
Ssch 0.05 0.12 0.05 1.19 1.86 2.76 0.42 0.11 
Sf 0.07 0.10 0.15 1.20 1.46 7.19 1.50 0.10 
Soil Dec 2007 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.15 0.10 0.06 1.10 0.99 1.96 1.00 0.10 
S2 0.19 0.09 0.10 1.02 1.09 4.32 1.00 0.15 
S3 0.10 0.19 0.05 1.92 1.28 3.27 0.50 0.10 
S4 0.12 0.09 0.03 1.27 1.35 2.91 6.00 0.20 
Sv2 0.17 0.20 0.05 1.05 1.01 2.71 2.50 0.20 
Ssch 0.11 0.06 0.07 1.65 0.96 2.91 0.42 0.20 
Sf 0.18 0.08 0.10 1.31 1.92 1.69 1.50 0.15 
Ssv1 0.16 0.01 0.20 1.00 1.00 1.20 4.10 0.25 
 
 
 
 
 
 
 
 
 
154 
 
 
Soil Feb 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.15 0.10 0.04 1.00 0.95 1.90 1.01 0.11 
S2 0.17 0.09 0.12 1.04 1.00 4.40 1.10 0.17 
S3 0.13 0.18 0.04 1.95 1.20 3.31 0.51 0.13 
Sv2 0.18 0.21 0.04 1.08 1.00 2.70 2.51 0.20 
S4 0.14 0.09 0.04 1.20 1.30 2.80 0.13 0.21 
Ssch 0.12 0.06 0.06 1.66 0.96 2.89 0.43 0.21 
Sf 0.15 0.01 0.11 1.10 1.93 1.22 0.55 0.28 
Soil Apr 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.22 0.10 0.11 4.56 2.54 8.11 1.01 0.20 
S2 0.34 0.05 0.13 4.92 9.74 19.21 1.20 0.16 
S3 0.30 0.05 0.21 3.07 5.61 10.21 0.60 0.10 
S4 0.49 0.12 0.11 4.01 6.21 5.99 0.99 0.09 
Sv2 0.32 0.06 0.16 3.71 8.01 6.15 2.00 0.20 
Ssch 0.35 0.17 0.09 3.61 6.36 6.05 1.00 0.09 
Sf 0.13 0.19 0.11 5.01 7.01 14.09 1.50 0.19 
Soil Jun 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.20 0.09 0.07 4.28 2.00 6.02 1.50 0.26 
S3 0.10 0.08 0.15 6.21 1.08 14.61 1.20 0.29 
Ssch 0.12 0.06 0.10 5.36 0.96 13.08 1.00 0.20 
S4 0.15 0.10 0.07 4.71 0.72 10.01 1.00 0.25 
Sv2 0.14 0.12 0.05 3.92 0.65 9.26 4.00 0.35 
Sf 0.16 0.09 0.12 4.77 4.01 8.99 1.55 0.30 
Soil Aug 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.21 0.09 0.07 4.30 2.20 6.01 1.70 0.29 
S2 0.10 0.07 0.15 6.20 1.09 13.49 1.20 0.30 
S3 0.21 0.07 0.16 6.20 1.09 14.60 1.30 0.30 
S4 0.14 0.09 0.06 4.80 0.73 10.00 1.00 0.26 
Ssch 0.13 0.05 0.09 5.36 0.98 13.10 1.20 0.21 
Sv2 0.16 0.13 0.07 3.56 0.66 9.20 4.25 0.36 
Sf 0.17 0.09 0.14 4.69 4.04 8.79 1.61 0.36 
Soil Oct 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.08 0.04 0.16 18.27 5.43 3.01 1.73 0.30 
S2 0.06 0.05 0.12 4.03 0.96 7.29 1.21 0.31 
S3 0.07 0.09 0.19 2.11 3.92 4.71 1.36 0.32 
S4 0.07 0.07 0.21 2.89 0.95 8.32 1.01 0.22 
Ssch 0.07 0.10 0.17 3.61 0.79 6.99 1.24 0.25 
Sv2 0.09 0.05 0.15 4.20 0.96 7.03 4.32 0.38 
Sf 0.04 0.08 0.11 2.61 3.07 6.12 1.65 0.39 
 
 
 
 
 
 
155 
 
 
 
 
 
Soil Dec 2008 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.09 0.03 0.14 9.20 5.40 3.00 1.70 0.40 
S2 0.08 0.04 0.11 4.01 0.99 7.30 1.20 0.32 
S3 0.05 0.08 0.21 2.01 3.90 4.75 1.39 0.33 
S4 0.06 0.05 0.24 2.90 0.96 8.30 1.09 0.40 
Ssch 0.06 0.13 0.17 3.02 0.78 7.01 1.20 0.29 
Sv2 0.06 0.06 0.14 4.10 0.99 6.02 4.30 0.40 
Sf 0.06 0.07 0.13 2.63 3.08 6.01 1.66 0.42 
Soil Feb 2009 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.08 0.02 0.10 8.10 4.50 3.10 1.60 0.50 
S2 0.06 0.02 0.12 4.03 0.89 7.00 1.21 0.33 
S3 0.05 0.08 0.22 2.02 3.50 4.60 1.40 0.33 
S4 0.07 0.06 0.26 2.96 0.99 8.31 1.00 0.40 
Ssch 0.08 0.16 0.19 3.02 0.87 4.01 1.21 0.30 
Sv2 0.07 0.06 0.16 4.00 0.98 6.00 4.31 0.55 
Sf 0.08 0.07 0.10 2.64 3.00 6.08 1.60 0.45 
Soil Apr 2009 
CODE Cr Cd Pd Zn Cu Mn Ni V 
S1 0.09 0.03 0.10 4.90 4.55 3.10 1.70 0.60 
S2 0.05 0.03 0.16 4.00 0.80 6.75 1.30 0.35 
S3 0.05 0.09 0.25 2.01 3.43 4.67 1.45 0.36 
S4 0.06 0.07 0.25 2.95 0.99 7.00 1.10 0.41 
Ssch 0.05 0.15 0.19 3.00 0.91 4.03 1.20 0.31 
Sv2 0.05 0.08 0.17 3.95 0.99 6.10 4.30 0.60 
Sf 0.09 0.07 0.12 2.71 3.10 6.00 1.61 0.45 
 
 
 
 
 
 
 
156 
 
 
 
Soil samples 
S1 S2 S3 S4 S5 S6 
Range Mean Range Mean Range Mean Range Mean Range Mean Range Mean 
Cr 0.06 –0.22 0.15±0.60 0.05 - 0.34  0.15±0.09 0.05 – 0.32 0.15±0.1 0.04 – 0.22 0.13±0.06 0.06 – 0.31 0.14±0.07 0.06 – 0.49 0.17±0.12 
Cd 0.02 - 0.15 0.08±0.04 0.02 – 0.13 0.07±0.04 0.05 – 0.19 0.1±0.04 0.01 – 0.19 0.1±0.05 0.01 – 0.11 0.08±0.03 0.05 - 21 0.1±0.05 
Pd 0.04-0.25 0.11±0.06 0.01-0.16 0.13±0.02 0.04-0.25 0.15±0.07 0.09-0.15 0.12±0.02 0.06-0.20 0.14±0.04 0.03-0.26 0.13±0.08 
Zn 1.00-18.27 5.08±4.86 1.02-6.21 3.7±1.66 1.71-6.21 2.69±1.49 1.10-5.01 2.73±1.41 0.98-5.34 2.85±1.71 1.08-4.80 29.64±1.41 
Cu 0.95-5.43 2.67±1.69 0.80-9.74 2.69±2.83 0.96-5.61 2.81±1.44 1.46-7.01 2.84±1.53 1.00-6.50 2.20±1.52 0.72-6.21 2.18±1.86 
Mn 1.90-8.11 4.49±2.07 4.32-19.21 10.07±4.65 3.27-14.60 8.18±4.30 1.22-14.09 7.68±4.06 1.20-10.74 5.64±2.91 2.70-14.00 8.26±3.33 
Ni 1.00-2.20 1.49±0.43 1.00-1.31 1.18±0.1 0.50-1.45 0.92±0.43 0.55-1.45 1.42±0.34 1.19-8.05 3.11±2.53 0.10-6.00 1.98±1.77 
V 0.10-0.60 0.27±0.17 0.20-0.40 0.24±0.08 0.10-0.40 0.22±0.10 0.10-0.40 0.27±0.14 0.20-0.40 0.26±0.11 0.10-0.40 0.24±0.09 
SO4 0.03-0.23 0.14±0.07 0.08-0.40 0.21±0.11 0.05-0.33 0.16±0.1 0.07-0.32 0.17±0.08 0.08-0.25 0.18±0.05 0.07-0.33 0.17±0.09 
NO3 0.03-0.20 0.1±0.05 0.10-0.31 0.17±0.07 0.05-0.36 0.18±0.10 0.05-0.21 0.11±0.05 0.08-0.21 0.15±0.43 0.05-0.35 0.15±0.09 
PO4 0.00-0.50 0.14±0.13 0.10-0.70 0.21±0.18 0.10-0.6 0.17±0.16 0.00-0.60 0.15±0.17 0.10-0.30 0.14±0.08 0.00-0.70 0.19±0.21 
pH 5.80-7.10 6.4±0.37 5.80-7.80 6.71±0.58 5.40-7.50 6.30±0.56 5.00-6.30 5.52±0.38 4.90-7.00 6.08±0.67 5.10-6.90 5.82±0.49 
K 0.10-0.10 0.09±0.01 0.10-0.10 0.09±0.01 0.10-0.10 0.09±0.01 0.10-0.10 0.09±0.01 0.10-0.10 0.09±0.01 0.10-0.10 0.08±0.02 
Na 0.03-0.05 0.04±0.01 0.02-0.06 0.04±0.01 0.03-0.05 0.04±0.01 0.03-0.06 0.04±0.01 0.03-0.33 0.04±0.09 0.02-0.06 0.05±0.01 
Ca 2.00-2.00 2.08±0.16 2.00-2.00 2.14±0.08 2.00-2.00 2.14±0.09 2.00-3.00 2.31±0.18 2.00-2.00 2.24±0.12 2.00-2.00 2.16±0.15 
TOM 1.34-3.10 1.72±0.48 1.34-2.50 1.77±0.35 1.34-4.50 2.00±0.84 1.05-4.62 2.45±1.28 1.63-4.48 2.65±1.0 1.21-4.41 2.96±1.29 
TOC 0.78-1.80 1.00±0.28 0.76-1.45 1.02±0.2 0.78-2.61 1.46±0.7 0.61-2.68 1.43±0.6 0.80-2.60 1.71±0.75 0.70-2.56 1.29±0.58 
THC 0.29-1.34 1.05±0.29 0.92-1.42 1.20±0.18 0.52-1.15 0.89±0.23 1.56-2.67 2.08±0.32 0.92-1.83 1.38±0.42 0.33-1.10 0.71±0.55 
    
III: Mean soil concentration of heavy metals and other parameters 
 
 Issues with V, PO4, pH, K and Ca 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
157 
 
Metals 
 
 
 
 
IV: Mean water concentration of heavy metals and other parameters 
 
Water  samples 
GW1 GW2 GW3 GW4 GW5 GW6 
Range Mean Range Mean Range Mean Range Mean Range Mean Range Mean 
Cr 0.00-0.09 0.4±0.03 0.01-0.09 0.03±0.02 0.01-0.17 0.05±0.05 0.01-0.09 0.04±0.02 0.05-0.09 0.06±0.02 0.01-0.01 0.04±0.03 
Cd 0.00-0.12 0.03±0.04 0.00-0.13 0.02±0.04 0.00-0.1 0.03±0.03 0.00-0.1 0.03±0.03 0.01-0.07 0.04±0.03 0.00-0.1 0.03±0.03 
Pd 0.01-0.08 0.03±0.03 0.01-0.08 0.03±0.02 0.00-0.08 0.03±0.03 0.00-0.15 0.04±0.05 0.02-0.06 0.04±0.02 0.00-0.11 0.03±0.03 
Zn 0.0-1.10 0.67±0.36 0.09-1.10 0.65±0.39 0.12-0.83 0.5±0.26 0.05-0.99 0.48±0.38 0.14-0.60 0.42±0.20 0.01-1.15 0.59±0.41 
Cu 0.04-0.45 0.21±0.14 0.04-0.37 0.21±0.12 0.01-0.31 0.17±0.11 0.05-0.25 0.16±0.08 0.01-0.20 0.12±0.08 0.05-0.27 0.19±0.14 
Mn 0.10-0.30 0.18±0.07 0.00-0.30 0.16±0.07 0.00-0.30 0.18±0.08 0.10-0.40 0.18±0.08 0.20-0.20 0.17±0.03 0.10-0.40 0.19±0.07 
Ni 0.20-1.00 0.62±0.36 0.10-0.90 0.51±0.39 0.10-0.60 0.29±0.14 0.10-1.60 0.76±0.69 0.20-0.30 0.26±0.04 0.00-0.60 0.26±0.24 
V 0.10-0.20 0.20±0.04 0.00-0.20 0.17±0.07 0.10-0.90 0.22±0.22 0.20-0.40 0.25±0.09 0.20-0.20 0.17±0.03 0.00-0.20 0.12±0.08 
SO4 0.05-0.19 0.11±0.04 0.05-0.14 0.09±0.03 0.06-0.19 0.12±0.05 0.04-0.16 0.10±0.05 0.02-0.07 0.04±0.02 0.07-0.21 0.16±0.05 
NO3 0.05-0.18 0.11±0.04 0.06-0.25 0.13±0.05 0.05-0.21 0.09±0.04 0.03-0.16 0.08±0.06 0.03-0.19 0.10±0.07 0.07-0.21 0.13±0.58 
PO4 0.00-0.20 0.1±0.05 0.00-0.20 0.11±0.05 0.00-0.20 0.12±0.04 0.00-0.20 0.14±0.09 0.00-0.10 0.08±0.04 0.00-0.20 0.09±0.04 
pH 5.0-6.13 5.7±0.35 3.47-6.80 6.0±0.9 35.96-6.89 6.45±0.29 5.10-6.89 5.73±0.54 5.06-5.60 5.43±0.25 5.43-7.71 6.10±0.69 
Temp 26.00-30.0 26.85±1.33 26.00-32.0 26.95±1.67 26.00-31.0 27.06±1.37 25.00-31.0 26.59±1.63 26.0-26.0 26.12±0.48 26.0-32.0 27.09±1.63 
TH 40-216 118.96±68. 46-240 137.05±75. 40-270  14-220    20-310  
80 25 
Alk             
Cond             
Cl             
THC             
Issues with PO4, pH, Alk, Cond, Cl and THC 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
158 
 
Metals 
 
 
 
 
             
 
 
             V: Table 
Metals Mean value Sign. 
showing the means 
 YR 1 YR2  
and ANOVA 
Cr 0.19±0.08 0.09±0.05 0.00 
of metals for soils 
(S -S ) in Cd 0.11±0.05 0.07±0.03 0.00 1 5 the two 
years  Pb 0.11±0.04 0.14±0.05 0.00 
 Zn 2.01±1.1 4.39±2.5 0.00 
 Cu 2.78±2.13 2.00±1.41 0.04 
 Mn 6.67±4.58 7.32±2.98 0.42 
 Ni 1.95±2.09 1.77±0.99 0.6 
 V 0.16±0.04 0.35±0.09 0.00 
 TPH 1.85±1.02 1.47±0.79 0.04 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
159 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
VI: Table showing the means and ANOVA of metals in soil samples, (S1-S5) and control soil 
(S6) during the study period 
 
Metals Soil Wet land samples Control samples Sign 
samples (S6) 
(S1-S5) 
Cr 0.14±0.74 1.4±0.08 0.14±0.08 0.73 
Cd 0.09±0.04 0.1±0.04 0.1±0.45 0.25 
Pb 0.13±0.04 0.11±0.05 0.14±0.08 0.4 
Zn 3.45±2.69 2.80±1.38 2.66±1.35 0.35 
Cu 2.68±1.83 1.86±1.83 2.08±1.8 0.15 
Mn 7.2±4.14 5.9±3.3 8.16±3.2 0.21 
Ni 1.61±1.33 2.46±2.11 1.91±1.7 0.1 
V 0.25±0.12 0.26±0.13 0.25±0.1 0.91 
TPH 1.33±0.5 2.96±0.56 0.67±0.31 0.00 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
160 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
VII: Table showing the means and ANOVA of metals, TPH and pH in surface water (SW1-SW2), 
ground water (GW1-GW5) and control ground water (GW6) 
 
Metals Ground water Ground water Surface water Sign. 
(GW1-GW5) control (GW6) (SW1-SW2) 
Cr 0.04±0.03 0.04±0.03 0.04±0.03 0.87 
Cd 0.03±0.03 0.03±0.03 0.03±0.03 0.85 
Pb 0.03±0.03 0.03±0.03 0.05±0.05 0.17 
Zn 0.57±0.34 0.6±0.41 0.88±1.03 0.15 
Cu 0.18±0.11 0.17±0.08 0.23±0.24 0.4 
Mn 0.17±0.07 0.19±0.07 0.15±0.07 0.43 
Ni 0.05±0.44 0.26±0.24 2.18±0.09 0.00 
V 0.21V0.12 0.12±0.08 0.26±0.05 0.01 
pH 5.82±1.04 6.10±0.68 5.28±0.4 0.04 
TPH 1.34±0.64 3.31±0.54 0.64±0.26 0.00 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
161