Geospatial Variability and Distribution of Total Petroleum Hydrocarbons (TPH) in Soot-Contaminated Rain and Rivers at Oyigbo, Niger Delta, Nigeria

Abstract

This comprehensive study delves into the analysis of Total Petroleum Hydrocarbon (TPH) concentrations in soot-contaminated rain and rivers within Oyigbo, Rivers State, Niger Delta, Nigeria, with a primary focus on unraveling the geospatial variability and distribution of TPH in the impacted water sources. The study adopts a multifaceted methodology, incorporating fieldwork, sampling, laboratory analysis, and geospatial mapping using ArcGIS 10.4 software to elucidate spatial variations. Results spotlight the highest rainwater TPH concentrations at MKT 7-Umuosi 2 Market (128.179 mg/L) and the lowest at SET 13-Okpontu Settlements (8.976 mg/L), situated in the Okoloma and Umu Agbai-Obete axis, respectively. Likewise, river water exhibits the highest TPH at RVR 5-Imo River (37.118 mg/L), and the lowest at RVR 6-Imo River (187.118 mg/L), at Okoloma and Umu Agbai-Obete axis. Analysis of the 41 samples indicates that 19 locations surpass the 50 mg/L acceptable limits set by the World Health Organization (WHO, 2017), and the Department of Petroleum Resources (DRP-EGASPIN, 2018), Nigeria standards, with 10 locations recording concentrations above, and 12 locations falling below 30 mg/L. These findings underscore approximately 46% exhibiting high, 24% displaying medium, and 29 % showcasing low concentrations across the study area, following a spatial pattern with higher pollution dispersion in the Northern and Northwestern regions at Okoloma and Obigbo axes, and lower pollution levels in the Eastern regions at Umu Agbai-Obete axis. In essence, this study provides a comprehensive insight into TPH in soot-contaminated water resources in Oyigbo, contributing significantly to the advancement of knowledge regarding spatial variation, distribution, and implications for water quality management. Furthermore, it serves as a valuable resource for policy development, offering evidence for targeted environmental programs and practical assistance to environmentalists, researchers, government agencies, and the public in the assessment and enhancement of water quality in affected communities.

Full text

This comprehensive study delves into the analysis of Total Petroleum Hydrocarbon (TPH)
concentrations in soot-contaminated rain and rivers within Oyigbo, Rivers State, Niger Delta,
Nigeria, with a primary focus on unraveling the geospatial variability and distribution of TPH in the
impacted water sources. The study adopts a multifaceted methodology, incorporating fieldwork,
sampling, laboratory analysis, and geospatial mapping using ArcGIS 10.4 software to elucidate
spatial variations. Results spotlight the highest rainwater TPH concentrations at MKT 7 - Umuosi
Journal of Geography, Environment and Earth Science
International
Volume 28, Issue 3, Page 1-30, 2024; Article no.JGEESI.113182
ISSN: 2454-7352
Geospatial Variability and Distribution
of Total Petroleum Hydrocarbons (TPH)
in Soot-Contaminated Rain and Rivers
at Oyigbo, Niger Delta, Nigeria
Nurudeen Onomhoale Ahmed a*,
Andrew Adesola Obafemi b and Godwin J. Udom c
a Institute of Natural Resources, Environment and Sustainable Development (INRES). University of
Port Harcourt, Rivers State, Nigeria.
b Department of Geography and Environmental Management, Faculty of Social Sciences. University
of Port Harcourt, Rivers State, Nigeria.
c Department of Geology, Faculty of Science. University of Port Harcourt, Rivers State, Nigeria.
Authors’ contributions
This work was carried out in collaboration among all authors. All authors read and approved the final
manuscript.
Article Information
DOI: 10.9734/JGEESI/2024/v28i3753
Open Peer Review History:
This journal follows the Advanced Open Peer Review policy. Identity of the Reviewers, Editor(s) and additional Reviewers,
peer review comments, different versions of the manuscript, comments of the editors, etc are available here:
https://www.sdiarticle5.com/review-history/113182
Received: 16/12/2023
Accepted: 22/02/2024
Published: 27/02/2024
ABSTRACT
*Corresponding author: E-mail: nurudeenonomhoale@gmail.com;
J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024
Original Research Article

Ahmed et al.; J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024; Article no.JGEESI.113182
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Keywords: Atmospheric soot; water contamination; TPH distribution; geospatial variability; Oyigbo;
Niger Delta; Nigeria.
1. INTRODUCTION
Water, as a fundamental resource, plays a
pivotal role in sustaining life and serves various
purposes such as agriculture, domestic use,
industrial processes, and recreation [1]. Its
quality is not only crucial for direct human
consumption but is also integral to ecosystem
services. In regions like the Niger Delta, the
nexus between water availability, distribution,
and spatial variation is particularly significant due
to the challenges posed by factors such as
population growth and industrialization [2,3].
The quality of the environmental system
including surface, groundwater and soils is
influenced by a myriad of factors, including both
natural processes and human activities [4,5]. In
petroleum-producing areas like the Niger Delta,
oil-related activities, such as gas flaring,
contribute to environmental pollution [6,7]. Gas
flaring, a common practice in the region, releases
pollutants like soot into the atmosphere,
impacting air quality and subsequently affecting
rainwater composition [8,9]. Rainfall, acting as a
natural cleansing process, collects pollutants
from the atmosphere, including total petroleum
hydrocarbons (TPH) [10]. Soot, a byproduct of
petroleum activities, poses health and
environmental risks, affecting air and water
quality [11].
Rainwater, a critical component of the
hydrological cycle, serves as a pathway for
pollutants present in the atmosphere, leading to
the contamination of water resources [12,13]. In
areas with extensive oil and gas activities, the
introduction of soot and other pollutants poses
health and environmental risks [14]. Therefore,
understanding the geospatial distribution and
variability of total petroleum hydrocarbons (TPH)
in soot-contaminated rain and river water is
imperative for assessing water quality in regions
like Oyigbo, Rivers State, Niger Delta, Nigeria.
Soot, generated from petroleum hydrocarbon
production and fossil fuel burning, is a significant
anthropogenic pollutant with adverse effects on
human health, visibility, ecosystems, agricultural
productivity, and global warming [15]. Soot, a
component of particulate matter, contains TPH,
which is harmful to human health and the
environment [16]. The presence of TPH,
encompassing various petroleum hydrocarbons,
adds complexity to the pollution landscape [17,6].
TPH includes potentially carcinogenic materials,
particularly polycyclic aromatic hydrocarbons
(PAHs), which are of concern due to their health
implications [18].
The study aims to comprehensively assess the
TPH concentrations in soot-contaminated rain
and rivers at Oyigbo, Rives State, Niger Delta,
Nigeria. It focuses on the geospatial variability
and distribution of TPH in the soot-contaminated
rain and river water. The Aliphatic Hydrocarbon
and Polycyclic Aromatic Hydrocarbon
concentrations were analyzed to assess the
contamination status of surface and rainwater,
providing insights into pollution hotspots and
vulnerability areas.
Market (128.179 mg/L) and the lowest at SET 13 - Okpontu Settlements (8.976 mg/L), situated in
the Okoloma and Umu Agbai-Obete axis, respectively. Likewise, river water exhibits the highest
TPH at RVR 5 - Imo River (37.118 mg/L), and the lowest at RVR 6 - Imo River (187.118 mg/L), at
Okoloma and Umu Agbai-Obete axis. Analysis of the 41 samples indicates that 19 locations
surpass the 50 mg/L acceptable limits set by the World Health Organization (WHO, 2017), and the
Department of Petroleum Resources (DRP - EGASPIN, 2018), Nigeria standards, with 10 locations
recording concentrations above, and 12 locations falling below 30 mg/L. These findings underscore
approximately 46% exhibiting high, 24% displaying medium, and 29 % showcasing low
concentrations across the study area, following a spatial pattern with higher pollution dispersion in
the Northern and North-western regions at Okoloma and Obigbo axes, and lower pollution levels in
the Eastern regions at Umu Agbai-Obete axis. In essence, this study provides a comprehensive
insight into TPH in soot-contaminated water resources in Oyigbo, contributing significantly to the
advancement of knowledge regarding spatial variation, distribution, and implications for water
quality management. Furthermore, it serves as a valuable resource for policy development, offering
evidence for targeted environmental programs and practical assistance to environmentalists,
researchers, government agencies, and the public in the assessment and enhancement of water
quality in affected communities.

Ahmed et al.; J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024; Article no.JGEESI.113182
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In conclusion, understanding the geospatial
distribution of TPH in soot-contaminated water
resources is vital for sustainable water
management in petroleum-producing areas. This
research is crucial for water quality management,
disease prevention, and environmental risk
mitigation in the region. This study contributes
valuable information to environmentalists,
researchers, government agencies, and the
public, aiding in the development of programs to
assess and improve water quality in affected
communities.
1.1 Study Area Description
1.1.2 Human geography of study area
Oyigbo, situated in the Niger Delta region of
Nigeria, is both a town and a Local Government
Area in Rivers State. This satellite town is
strategically positioned approximately 30
kilometers northeast of Port Harcourt, falling
within the geographic coordinates of latitude
4˚54' to 4˚46' N and longitude 7˚15' to 7˚25' W.
Encompassing a total area of 248.00 km² (95.75
sq mi) (Fig. 1), Oyigbo plays a significant role in
the regional landscape of Rivers State.
Established in 1991, Oyigbo Local Government
Area has its administrative headquarters located
in Afam, commonly referred to as Okoloma-
Ndoki. This administrative unit was carved out of
Khana/Oyigbo Local Government in Rivers State.
Oyigbo shares its boundaries with Khana to the
Southeast, Tai to the South, Eleme and
Obio/Akpor to the Southwest, while the entire
Northern part is bounded by Abia State. The
geographical composition of Oyigbo is
characterized by its division into two distinct
zones or regions, primarily inhabited by the Asa
and Ndoki people [19]. This local government
area occupies a pivotal position in the
sociopolitical and economic dynamics of Rivers
State, contributing to the diverse cultural and
environmental tapestry of the Niger Delta region.
Rivers State, a prominent state in the Niger Delta
region of Nigeria, is geographically surrounded
by Imo State to the North, Delta State to the
North-west, Akwa Ibom to the South-east, Abia
State to the East, and Bayelsa State to the
South-west. This strategic location places Rivers
State at the heart of the Niger Delta, a region
characterized by its rich cultural diversity and a
mosaic of numerous ethnic groups. Within Rivers
State, the Oyigbo area stands out as a hub of
ethnic vibrancy, with various communities
representing ethnicities such as Ekpeye, Andoni,
Ikwerre, Ndoni, and the Ogoni. Among these
groups, the Ikwerre people are the predominant
ethnic community in the Oyigbo area [19].
The towns and communities within the Oyigbo
Local Government Area are outlined in Table 1,
depicting the varied regions that constitute this
dynamic part of Rivers State. The population
trends over the years, as highlighted in Table 2,
reveal a notable increase from 40,407 in 1975 to
125,666 in 2015. This demographic surge is
accompanied by a rise in population density,
escalating from 163.1 km² in 1975 to 507.3 km²
in 2015. The demographic dynamics of the
Oyigbo area are intricately linked to the
abundance of dry land and the unique terrain of
the region. The population distribution in 2015 is
further delineated, with 63,575 males and 62,091
females contributing to the vibrant demographic
landscape of Oyigbo. This data provides a
comprehensive snapshot of the population
growth and composition, shedding light on the
socio-economic and environmental factors
shaping the Oyigbo area within the broader
context of Rivers State [20].
1.2 Physical Geography of Study Area
The Oyigbo area is characterized by a tropical
wet climate, with prolonged and intense rainy
seasons and brief dry seasons. The dry season
is confined to the months of November,
December, January, and February. While the
harmattan, a significant climatic feature in West
Africa, has a milder impact on Oyigbo compared
to other regions, the area experiences its
heaviest precipitation in September, with an
average of 370 mm of rain. Conversely,
December stands out as the driest month,
witnessing an average rainfall of 20 mm [21].
Temperature variations are minimal throughout
the year, with average temperatures ranging
between 25°C and 28°C. The hottest months
span from February to May, featuring a marginal
temperature difference of 2°C between these
months. Relative humidity averages around 80
percent during the rainy season and drops to
approximately 40 percent in the dry season, with
high humidity prevailing for 8-10 months (March
to November) and sometimes persisting
throughout the year [21].
Situated in the equatorial rainforest belt of
Nigeria, Oyigbo experiences a monthly mean
temperature ranging from 25 to 28.5°C and an
annual mean rainfall of about 2500 mm, with the
majority occurring between May and October

Ahmed et al.; J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024; Article no.JGEESI.113182
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[22,23] (Fig. 2). The rainfall distribution pattern
showcases two lows in November and December
and a second minimum in August, linked to the
August break. From February to June and July,
total rainfall rises steeply, reaching the primary
maximum, followed by a second high in
September and a decrease in November and
December [22]. (Fig. 3 and 4). The dominant
vegetation in the area comprises tropical
rainforest or riparian vegetation, particularly
along the river systems, and secondary bush
resulting from farming or fallowing. The forest
includes a first canopy with plants exceeding 40
meters, a middle canopy ranging from 15 to 40
meters, and mangrove shrubs reaching
approximately 15 meters [21].
Fig. 1. Map of rivers state showing the study area
(Source: Digitized by Author)

Ahmed et al.; J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024; Article no.JGEESI.113182
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4000
3500
3000
2500
2000
1500
1000
500
0
Mean Annual Rainfall (mm)
Table 1. Towns/Communities of Oyigbo L.G.A. Zones/Regions
S/No
Asa Region / District / Zone
Ndoki Region / District / Zone
1
Obigbo
Afam Uku
2
Kom Kom
Afam Nta
3
Izuoma
Ayama
4
Obeama
Azuogu
5
Nmirinwayi
Egberu
6
Mgboji
7
Marihu
8
Obeakpu
9
Obete
10
Obunku
11
Okoloma
12
Okpontu
13
Umuagbai
14
Umuosi
Table 2. Population of Oyigbo from 1975 to 2015
Data
S/N
1975
1
1990
2
2000
3
2015
4
Population
40,407
63,533
82,697
125,666
Population Density
163.1/km2
256.5/km2
333.9/km2
507.3/km2
Source: NPC, 2006
Fig. 2. Mean annual rainfall for Niger Delta
(Source: Adejuwon et al., [22])
The area boasts a rich variety of plants, including
economic, medicinal, and food crops like palm
trees and raffia palms. Originally abundant in
economic trees, especially oil palms, the riverine
areas feature freshwater swamp trees, palms,
shrubs, and mangroves in beach ridge zones
and tidal flats [24]. The topography of Oyigbo is
characterized by sub-horizontal and gently
sloping terrain. The wind predominantly blows
from the South-West to North-West, with South-
West being the most forceful direction [25].
Rainfall occurs for approximately ten months a
year, with varying intervals. The region exhibits
poor drainage due to a combination of low relief,
high water table, and high rainfall, resulting in
seasonally flooded Local Government Areas
(LGAs) that impact agriculture and development
activities.
mm

Ahmed et al.; J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024; Article no.JGEESI.113182
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Opobo
Onne
Degema
Port-Harcourt
Ahoada
Yenagoa
Forcados
Warri
Sapele
0
20
40
60
80
100
120
Fig. 3. Wet season rainfall amount (Feb/Mar-Nov) for Niger Delta
(Source: Adejuwon et al., [22])
Fig. 4. Dry season rainfall amount (Dec-Jan/Feb) for Niger Delta
(Source: Adejuwon et al., [22])
The coastal plain, with an elevation of about
139m above sea level, comprises low-lying
plains, swamps, creeks, and waterways. The
land surface gently slopes (3-5 degrees on
average) in the northwest to southeast direction
[26]. The most significant water resource in
Oyigbo L.G.A. is the Imo River, originating in
Umuaku village and flowing through Abia, Imo,
Rivers, and Akwa Ibom states. The Imo River,
with three main tributaries (Aba River, Otamiri
River, and Oramirukwa River), empties into the
Atlantic Ocean through wide estuaries in Rivers
State. The Imo River's estuary, approximately
40km wide, has an average discharge of
4000m3/s and encompasses 26,000 hectares of
wetland. This vital water source supports the
daily activities of communities along its banks
and tributaries [27].
2. METHODOLOGY
2.1 Fieldwork and Sampling
The research involved the analysis of a total of
41 water samples, comprising 34 rainwater
samples and 7 surface water samples. Fig. 5 and
Table 3 provide details on the locations and
specific points from which the rain and river
water samples were collected. Rainwater
collection was conducted directly as precipitation
occurred, employing a purpose-built rainwater
harvesting system consisting of receptor bottles
with large funnel-tops. These rain harvesting
apparatuses were strategically mounted on
power grid poles to ensure a random yet uniform
distribution across the study area. All utilized
bottles underwent pre-sterilization. The collected
Opobo
Onne
Degema
Port-Harcourt
Ahoada
Yenagoa
Forcados
Warri
Sapele
0
500 1000 1500 2000 2500 3000 3500 4000

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rainwater was then transferred from the receptor
bottles to 1.5-liter plastic water sampling
containers. In parallel, surface water samples
were directly obtained from community rivers
within the study area. The communities and
locations were categorized into five study axes:
Obigbo, Komkom-Obiama, Okoloma, Egberu,
and Umu Agbai-Obete, to facilitate the sampling
and identification processes. Geo-referencing of
all sampling points was accomplished using the
Garmin eTrex 32x, a rugged Handheld Global
Positioning System (GPS). Additionally, on-site
visual field observations were conducted and
diligently recorded in the field notebook. A
camera was employed to capture photographic
evidence of crucial features and activities that
could potentially serve as primary sources of
water pollutants. This multifaceted approach
aimed to ensure a thorough and well-
documented sampling process for subsequent
analysis in the laboratory. The fieldwork was
conducted during the last quarter of 2021 and the
first quarter of 2022.
Fig. 5. Sampling points for the study area
(Source: Digitized by Author)
Table 3. Rain and river water sample location points
Sample
Number
Study
Axis
Sample
Location
Sample
Type
Sample
ID
Coordinates
Latitude Longitude
(N) (E)
SN 1
Model Primary Health
Rain
HSP 1
4° 52' 7° 06'
Care Centre
34.7984" 48.9204"
SN 2
Timber Market
Rain
MKT 1
4° 52' 7° 07'
23.4361" 03.3718"
SN 3
Obigbo
Obigbo Main Market
Rain
MKT 2
4° 52' 7° 08'
41.7036" 44.7853"

Ahmed et al.; J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024; Article no.JGEESI.113182
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Sample
Number
Study
Axis
Sample
Location
Sample
Type
Sample
ID
Coordinates
Latitude Longitude
(N) (E)
SN 4
Atata Market / Express
Rain
MKT 3
4° 53' 7° 07'
Bus Stop Area
01.5396" 50.0344"
SN 5
Umuebele Market
Rain
MKT 4
4° 53' 7° 08'
55.7502" 11.1926"
SN 6
Community Secondary
Rain
SCH 1
4° 52' 7° 07'
School, Umundinor
53.0860" 36.2982"
SN 7
Community Secondary
Rain
SCH 2
4° 52' 7° 07'
School, Umuakpahu
55.8332" 36.0624"
SN 8
Oasis of Love Orphanage
Rain
SET 1
4° 53' 7° 06'
Settlement
32.2656" 29.9628"
SN 9
Shell Flow Station
Rain
FCLT 1
4° 53' 7° 07'
Umuebele 4
31.9279" 21.5270"
SN 10
Otamiri River – Umuebele
River
RVR 1
4° 54' 7° 08'
1
11.6281" 26.3642"
SN 11
Otamiri River – Umuebele
River
RVR 2
4° 54' 7° 08'
2
18.2052" 22.0704"
SN 12
Imo River – Obigbo/Abia
River
RVR 3
4° 53' 7° 08'
Bridge
22.0646" 41.4646"
SN 13
Konko Market
Rain
MKT 5
4° 51' 7° 10'
22.8564" 56.0604"
SN 14
Komkom-
Obiama
Community Secondary
School, Komkom
Rain
SCH 3
4° 51' 7° 10'
28.0440" 31.0296"
SN 15
Lekuma-Obiama
Rain
SET 2
4° 51' 7° 11'
Settlement
05.1120" 36.7692"
SN 16
Komkom Settlement
Rain
SET 3
4° 51' 7° 09'
28.2340" 33.6122"
SN 17
Obiama Settlement
Rain
SET 4
4° 50' 7° 11'
30.9264" 38.3784"
SN 18
Imo River – Obiama
River
RVR 4
4° 51' 7° 11'
33.1020" 45.8196"
SN 19
Okoloma Market
Rain
MKT 6
4° 50' 7° 14'
59.6040" 45.1680"
SN 20
Okoloma
Umuosi Market
Rain
MKT 7
4° 51' 7° 17'
47.6820" 52.4328"
SN 21
Ayama Settlement
Rain
SET 5
4° 51' 7° 15'
09.7200" 51.0840"
SN 22
Afam Settlement /
Rain
SET 6
4° 51' 7° 14'
Roundabout Area
04.5000" 15.0360"
SN 23
Obumku Settlement
Rain
SET 7
4° 51' 7° 16'
33.0120" 54.4080"
SN 24
Okoloma Gas Plant
Rain
FCLT 2
4° 50' 7° 15'
40.2182" 12.6145"
SN 25
Afam Power Plant
Rain
FCLT 3
4° 50' 7° 15'
53.4408" 24.7500"
SN 26
Imo River – Okoloma
River
RVR 5
4° 51' 7° 13'
11.6640" 27.6132"
SN 27
Ndoki Health Care Centre
Rain
HSP 2
4° 51' 7° 19'
07.6284" 06.1212"
SN 28
Egberu
Ndoki Market
Rain
MKT 8
4° 50' 7° 19'
56.6016" 36.9012"
SN 29
Ndoki Comprehensive
Rain
SCH 4
4° 50' 7° 19'
School
59.5212" 27.8616"
SN 30
Afam-Uku Settlement
Rain
SET 8
4° 49' 7° 19'

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Sample
Number
Study
Axis
Sample
Location
Sample
Type
Sample
ID
Coordinates
Latitude
(N)
Longitude
(E)
00.0120"
00.0120"
SN 31
Egberu-Ndoki Settlement
Rain
SET 9
4° 48'
35.3562"
7° 16'
48.6335"
SN 32
Afam-Nta Settlement
Rain
SET 10
4° 48'
24.8508"
7° 20'
32.4888"
SN 33
Ban-Lori Market
Rain
MKT 9
4° 48'
22.7520"
7° 25'
55.2720"
SN 34
Obete Settlement
Rain
SET 11
4° 48'
39.4920"
7° 29'
14.0640"
SN 35
Umu
Agbai-
Obete
Umu Agbai Settlement
Rain
SET 12
4° 51'
12.3480"
7° 22'
38.5680"
SN 36
Okpontu Settlement
Rain
SET 13
4° 50'
05.7480"
7° 27'
31.8240"
SN 37
Azuagu Settlement
Rain
SET 14
4° 50'
51.3564"
7° 23'
35.3868"
SN 38
Marihun Settlement
Rain
SET 15
4° 50'
46.5900"
7° 25'
22.3824"
SN 39
Azumini Settlement
Rain
SET 16
4° 49'
07.4748"
7° 28'
29.6976"
SN 40
Imo River – Umu Agbai
River
RVR 6
4° 51'
27.9180"
7° 22'
19.8588"
SN 41
Imo River – Okpontu
River
RVR 7
4° 50'
35.8152"
7° 27'
01.5552"
2.2 Total Petroleum Hydrocarbon (TPH)
Analysis
The assessment of TPH content in the water
samples aimed to evaluate the concentrations of
both petroleum aliphatic hydrocarbons and
petroleum aromatic hydrocarbons present in the
samples. For this purpose, Gas Chromatography
Analysis was conducted using an Agilent 7820A
gas chromatograph (GC) equipped with a flame
ionization detector and an HP-5 fused silica
capillary column (30m × 0.32 mm ID × 0.25 μm
film thickness). The purified sample extracts
underwent detailed analysis, employing helium
as the carrier gas with a flow rate of 1.75 mL/min
and an average velocity of 29.47 cm/sec.
Injection occurred in splitless mode with a
precisely measured 1 μL of the sample extract
injected at a temperature of 300°C. The column
temperature was initially set at 40°C for 1 minute,
then increased at a rate of 7°C/min until reaching
320°C. The detector temperature was maintained
at 300°C throughout the analysis, following the
methodology outlined by Kim, Hong, and Won
[28] and Inyang, Aliyu and Oyewale [29].
Calibration of the GC was performed using
petroleum hydrocarbon calibration working
standards prepared within the range of 0.05–20
μg/mL, with n-hexane as the diluent. Calibration
curves were constructed, and average response
factors for each analyte were generated using
Agilent Chemstation chromatography software.
These curves demonstrated linearity, with
correlation coefficients ranging from 0.9846 to
0.9919. To quantify unresolved peaks, the
response factor of nC-15 was employed following
the approach outlined by Luan and Szelewski
[30]. The determination of TPH content involved
integration with baseline holding and peak sum
slicing, encompassing the concentrations of n-
alkanes eluting from nC-9 to nC-36, as well as
the unresolved complex mixture (UCM). Data
analysis utilized Agilent software to obtain ratios
of low molecular n-alkanes to high molecular n-
alkanes and unresolved n-alkanes to resolved n-
alkanes, as elucidated by Inyang et al. [29]. This
comprehensive analytical approach ensured
accurate quantification and characterization of
the total petroleum hydrocarbon content in the
water samples.
2.3 Geospatial Pollutant Mapping
The concentrations of Total Petroleum
Hydrocarbons (TPH) at each location were
spatially represented using ArcGIS 10.4
software. This tool integrated the TPH analysis
results of both rain and river water samples

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collected from various sampling points in Oyigbo
Local Government Area. The software processed
these data as input variables, employing
algorithms to generate graphical representations
such as curves or contours, effectively illustrating
the spatial distribution of water pollutant levels in
the studied region.
3. RESULTS AND DISCUSSION
3.1 Total Petroleum Hydrocarbons (TPH)
Distribution
To facilitate the analysis of total petroleum
hydrocarbon (TPH) content variability in rain and
water samples, the analyzed Total Aliphatic
Hydrocarbons (TAH) encompassing C8 to C40,
along with Pristane and Phytane, were
strategically grouped into three classes for easier
characterization. These categories and broad
classification were adopted for this study based
on the distinctive names and properties of
individual hydrocarbons within each group, and
providing a general categorization based on the
number of carbon atoms in the molecular
structure, although the properties of individual
hydrocarbons within each group can vary based
on factors such as branching and molecular
arrangement [31].
The categorization of aliphatic hydrocarbons
from C8 to C40 is undertaken with a focus on
their molecular weight, recognizing that the
weight of hydrocarbons increases with the
number of carbon atoms. The adopted general
grouping based on this study is structured as the
Lighter Aliphatic Hydrocarbons (C8 to C16), with
relatively lower molecular weights compared to
their heavier counterparts. Medium Aliphatic
Hydrocarbons (C17 to C24), including Pristane
and Phytane, this group falls within the
intermediate molecular weight range. Heavy
Aliphatic Hydrocarbons (C25 to C40), consisting
of hydrocarbons with higher molecular weights
when contrasted with lighter aliphatic
hydrocarbons [31].
Tables 4a, 4b, 4c, 4d, and 4e present a summary
of the Aliphatic Hydrocarbon and Polycyclic
Aromatic Hydrocarbon (PAH) contents in rain
and river water samples from study locations.
This presentation summarizes the maximum,
minimum, and mean of TPH at distinct axes,
offering an understanding of the hydrocarbon
distribution within the studied environmental
matrices.
Fig. 6a, 6b, 6c, 6d and 6e provide a
detailed distribution chart of Aliphatic
Hydrocarbon contents in rain and river
water samples gathered from various
locations based on the study axis. The X-axis of
the chart corresponds to the sample
locations and description, and the Y-axis
displays the corresponding hydrocarbon
concentrations.
Table 4a. TPH Content for Obigbo Study Axis (mg/L)
Mean
Max
Min
C8 to C16
7.510
21.916
1.349
C17 to C24
14.940
25.780
6.665
C25 to C40
43.414
74.204
13.625
PAH
2.239
4.862
0.681
Table 4b. TPH Content for Komkom-Obiama Study Axis (mg/L)
Mean
Max
Min
C8 to C16
0.486
5.511
2.324
C17 to C24
1.214
32.165
12.028
C25 to C40
7.103
26.720
18.984
PAH
0.459
2.878
1.581
Table 4c. TPH Content for Okoloma Study Axis (mg/L)
Mean
Max
Min
C8 to C16
7.836
25.144
0.014
C17 to C24
15.010
24.897
1.417
C25 to C40
58.568
95.464
18.574
PAH
3.048
4.899
0.947

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Table 4d. TPH Content for Egberu Study Axis (mg/L)
Mean
Max
Min
C8 to C16
5.7305
12.77
0.097
C17 to C24
16.739
24.107
6.231
C25 to C40
20.789
56.027
4.982
PAH
1.531
3.687
0.568
Table 4e. TPH Content Umu Agbai-Obete Study Axis (mg/L)
Mean
Max
Min
C8 to C16
1.480
8.275
0.1056
C17 to C24
7.223
22.862
1.497
C25 to C40
14.104
36.186
0.844
PAH
1.0167
2.591
0.241
Fig. 6a. Aliphatic Hydrocarbons Distribution Chart for Obigbo Study Axis
The charts give a clear and depictive summary of
the varying concentrations of TAH components
and categories, offering an understanding of the
hydrocarbon distribution within the studied
environmental matrices. The components,
classified into Light Aliphatic Hydrocarbons (C8
to C16) displayed by the green bar, Medium
Aliphatic Hydrocarbons (C17 to C24, Pristane,
and Phytane) represented with the blue bar, and
Heavy Aliphatic Hydrocarbons (C25 to C40)
indicated by the yellow-colored bar, reveal
distinctive patterns and total concentration (mg/L)
distributions for each sample across the study
locations.
For C8 to C16 components, the highest
concentrations were observed at SN 26 - RVR 5
(25.144 mg/L), SN 7 - SCH 2 (21.916 mg/L), SN
9 - FCLT 1 (14.746 mg/L), SN 28 - MKT 8 (12.77
mg/L), SN 20 - MKT 7 (10.964 mg/L), and SN 10
- RVR 1 (10.879 mg/L). Lower concentrations in
this category between 30 mg/L to 10 mg/L values
were generally scattered across different
samples with SN 31 - SET 9 (0.097 mg/L), SN 30
- SET 8 (0.98 mg/L), and SN 21 - SET 5 (0.721
mg/L) being the lowest distribution with values
below 10 mg/L concentration.
In the C17 to C24 range, SN 18 - RVR 4 (32.165
mg/L), SN 23 - SET 7 (24.897 mg/L), SN 29 -
Obigbo Axis
80
70
60
50
40
30
20
10
0
(HSP 1) (MKT 1) (MKT 2) (MKT 3) (MKT 4) (SCH 1) (SCH 2) (SET 1) (FCLT 1) (RVR 1) (RVR 2) (RVR 3)
SN 1 SN 2 SN 3 SN 4 SN 5 SN 6 SN 7 SN 8 SN 9 SN 10 SN 11 SN 12
C8 to C16 C17 to C24 C25 to C40
mg\L

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SCH 4 (24.107 mg/L), SN 25 - FCLT 3 (23.004
mg/L), SN 41 - RVR 7 (22.862 mg/L), SN 27 -
HSP 2 (20.838 mg/L), SN 26 - RVR 5 (22.444
mg/L), and SN 20 - MKT 7 (20.322 mg/L),
displayed the highest values, while various
samples exhibited concentrations between 20
mg/L to 5 mg/L. The lowest concentration
distributions in the medium TAH components
were recorded at SN 38 - SET 15 (1.497 mg/L),
SN 21 - SET 5 (1.417 mg/L), and SN 17 - SET 4
(1.214 mg/L). For C25 to C40 components, SN
20 - MKT 7 (93.966 mg/L), SN 25 - FCLT 3
(88.131 mg/L), SN 26 - RVR 5 (87.464 mg/L), SN
2 - MKT 1 (74.204 mg/L) and SN 4 - MKT 3
(71.756 mg/L) showed the highest
concentrations, with distributions in values
between 70 mg/L and 10 mg/L across different
samples, while the lowest values were recorded
at SN 17 - SET 4 (7.103 mg/L), SN 31 - SET 9
(5.005 mg/L), SN 35 - SET 12 (3.464 mg/L), and
SN 36 - SET 13 (0.844 mg/L).
Examining Pristane concentrations, the peaks
were observed at SN 19 - MKT 6 (2.885 mg/L),
SN 22 - SET 6 (2.852 mg/L), SN 16 - SET 3
(2.623 mg/L), SN 29 - SCH 4 (2.62 mg/L), SN 18
- RVR 4 and SN 26 - RVR 5 at 2.107 mg/L, SN
13 - MKT 5 (1.836 mg/L), and SN 5 - MKT 4
(1.724 mg/L). Conversely, the lowest values were
observed in SN 31 - SET 9 (0.059 mg/L), SN 8 -
SET 1, SN 15 - SET 2, SN 17 - SET 4, also SN
37 - SET 14 recorded concentrations of 0.42
mg/L, while SN 35 - SET 11 has no presence of
Pristane. For Phytane concentrations distribution,
SN 25 - FCLT 3 (1.400 mg/L), SN 7 - SCH 2
(2.320 mg/L), SN 8 - SET 1 (1.487 mg/L) and SN
15 - SET 2 at 2.487 mg/L represented the
highest value. Several locations across the study
area recorded Phytane distribution values within
the ranges of 1.0 mg/L to 0.1 mg/L, while SN -
MKT 1, SN 31 - SET 9, SN 32 - SET 10, SN 33 -
MKT 9, and SN 36 - SET 13 presented no
presence of Phytane.
In the comprehensive assessment of the entire
study area and specific axes, it is evident that the
concentration and distribution of hydrocarbon
components in the C25 to C40 range are the
highest, followed by C17 to C24, while the least
distribution is observed in the C8 to C16 range.
Within the Obigbo Axis, MKT 1 exhibits the
highest distribution, followed by MKT 3, with SCH
1 displaying the least distribution. In the
Komkom-Obiama Axis, RVR 4 and SET 3
demonstrate the highest distribution, while SET 4
displays the least distribution. Moving to the
Okoloma Axis, RVR 7, MKT 7, and FCLT 3
represent the highest distribution, while SET 5
reflects the least distribution. In the Egberu Axis
of the study, HSP 2 exhibits the highest
distribution, whereas SET 8 and SET 9 display
the least distribution.
Fig. 6b. Aliphatic Hydrocarbons Distribution Chart for Komkom-Obiama Study Axis
Komokom-Obiama Axis
35
30
25
20
15
10
5
0
(MKT 5)
(SCH 3)
(SET 2)
(SET 3)
(SET 4)
(RVR 4)
SN 13
SN 14
SN 15
SN 16
SN 17
SN 18
C8 to C16 C17 to C24 C25 to C40
mg/L

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Fig. 6c. Aliphatic Hydrocarbons Distribution Chart for Okoloma Study Axis
Fig. 6d. Aliphatic Hydrocarbons Distribution Chart for Egberu Study Axis
Notably, the Umu Agbai-Obete Axis stands out as
the area with the least distribution of Aliphatic
Hydrocarbons across all locations studied. Within
this axis, RVR 7 has the highest concentration,
while SET 12, and SET 13 represent the least
Total Aliphatic Hydrocarbon (TAH) distributions.
These detailed findings provide valuable insights
into the spatial variations of hydrocarbon
components, emphasizing specific areas with
elevated concentrations and others with
lower distribution within the studied regions and
axes.
Okoloma Axis
120
100
80
60
40
20
0
(MKT 6) (MKT 7) (SET 5) (SET 6) (SET 7) (FCLT 2) (FCLT 3) (RVR 5)
SN 19
SN 20
SN 21
SN 22
SN 23
SN 24
SN 25
SN 26
C8 to C16 C17 to C24 C25 to C40
Egberu Axis
60
50
40
30
20
10
0
(HSP 2)
(MKT 8)
(SCH 4)
(SET 8)
(SET 9)
(SET 10)
SN 27
SN 28
SN 29
SN 30
SN 31
SN 32
C8 to C16 C17 to C24 C25 to C40
mg/L
mg/L

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Fig. 6e. Aliphatic Hydrocarbons Distribution Chart for Umu Agbai-Obete Study Axis
Overall, in the rainwater samples, the Total
Aliphatic Hydrocarbons (TAH) exhibited its
highest concentration, reaching 128.197 mg/L at
location 20 (MKT 7), while the lowest value,
recorded at 8.976 mg/L, was observed at
location 36 (SET 13). Meanwhile, in the river
water samples, the maximum TAH value of
137.397 mg/L was noted at location 26 (RVR 5),
and the minimum, at 37.118 mg/L, was recorded
at location 40 (RVR 6). These categorizations
provide a clear understanding of hydrocarbon
distribution patterns across different aliphatic
components in the sampled locations, providing
valuable insights into the pollution intensity and
potential sources of hydrocarbon contamination
in the study area and emphasizing the need for a
comprehensive understanding of hydrocarbon
distribution across the sampled locations for
effective environmental assessment.
The distributions of Polycyclic Aromatic
Hydrocarbon (PAH) components in various
samples collected from distinct locations,
generally has most of the sample falling below
1.0 mg/L concentrations with only 12 samples
above the value. Fig. 7a, 7b, 7c, 7d, and 7e
illustrate the comprehensive distribution chart for
the entire Polycyclic Aromatic Hydrocarbon
(PAH) components. The distribution is depicted
hierarchically, presenting the values in a ring
format to facilitate a comparative analysis of the
concentration proportions across distinct
hierarchical levels. Anthracene reached the
highest concentration at SN 10 - RVR 1 (0.410
mg/L), and SN 41 - RVR 7 (0.210 mg/L). Pyrene
exhibited its highest concentration at SN 4 - MKT
3 (0.271 mg/L), while multiple samples had no
detectable levels. Chrysene concentrations were
highest at SN 5 - MKT 4 (0.359 mg/L), with
several samples containing no detectable levels.
Fluoranthene concentrations peaked at SN 2 -
MKT 1 (1.180 mg/L), while multiple samples
showed no presence. Benzo [a] Anthracene
displayed its highest concentration at SN 30 -
SET 3 (0.370 mg/L). Benzo [b] Fluoranthene
concentrations were highest at SN 32 - SET 10
(1.042 mg/L), and SN 5 - MKT 4 (1.0 mg/L),
while multiple samples had no detectable levels.
Benzo [k] Fluoranthene exhibited its highest
concentration at SN 24 - FCLT 3 (1.254 mg/L),
SN 22 - SET 6 (1.043 mg/L), and SN 21 - SET 5
(1.032 mg/L) with various samples containing no
detectable levels. Benzo [a] Pyrene reached its
highest concentration at SN 13 - MKT 5 (1.270
mg/L), SN 1 - HSP 1 (1.050 mg/L), and SN 15 -
SET 2 (1.001 mg/L), while multiple samples
showed no presence. Indenol [1,2,3, cd] pyrene
concentrations peaked at SN 9 - FCLT 1 (1.103
mg/L), SN 5 - MKT 4 (1.059 mg/L), SN 16 - SET
3 (1.050 mg/L), SN 36 - SET 13, and SN 24 -
FCLT 2 at 1.00 mg/L, with multiple samples
containing no detectable levels.
Umu Agbai-Obete Axis
40
35
30
25
20
15
10
5
0
(MKT 9) (SET 11) (SET 12) (SET 13) (SET 14) (SET 15) (SET 16) (RVR 6) (RVR 7)
SN 33 SN 34 SN 35 SN 36 SN 37 SN 38 SN 39 SN 40 SN 41
C8 to C16 C17 to C24 C25 to C40
mg/L

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Fig. 7a. PAH Distribution Chart for Obigbo Study Axis
Fig. 7b. PAH Distribution Chart for Komkom-Obiama Study Axis
Dibenzo [a,h] Anthracene recorded the highest
concentration distributions in all the PAH
components with highest value at SN 24 - FCLT
2 (2.211 mg/L), while multiple samples showed
concentrations above 1.0 mg/L. The PAH
distributions across various study axes exhibit
consistent trends, showcasing distinct regions
with higher concentrations sharing similar
contamination levels. Conversely, areas with
lower concentrations display analogous levels,
as evident in the charts.
In the Obigbo Axis, four locations, MKT 4, FCLT
1, SET 1, and MKT 1, comprise most PAH

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concentrations, covering over half of the
distribution across the axis. The remaining eight
locations represent less than half of the
distribution, with SCH 1 exhibiting the lowest
concentration in the axis. Similarly, the Komkom-
Obiama Axis demonstrates comparable trends,
where two locations, MKT 5 and SET 2, carry
most PAH concentrations, while the remaining
four locations, SET 3, RVR 4, SET 4, and
SCH 3, represent less than half of the distribution
in the axis. In the Okoloma Axis, three
locations, FCLT 2, SET 5, and SET 6,
account for more than half of the distribution,
leaving the remaining five locations
with concentrations below half of the overall
levels.
Fig. 7c. PAH Distribution Chart for Okoloma Study Axis
Fig. 7d. PAH Distribution Chart for Egberu Study Axis

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Fig. 7e. PAH Distribution Chart for Umu Agbai-Obete Study Axis
Moving to the Egberu Axis, two locations, SET
10 and MKT 8, occupy two-thirds of the entire
region, while the remaining four locations, SET 8,
HSP 2, SET 9, and SCH 4, share the rest of the
distribution. In the Umu Agbai-Obete Axis, nine
locations are observed, with three of them, SET
13, RVR 7, and SET 15, occupying more than
half of the distribution in the region. The
remaining six locations, SET 15, RVR 6, MKT 9,
SET 12, SET 14, and SET 11, have lower
concentrations, with SET 11 having the least
levels. Generally, Naphthalene,
Methylnaphthalene, Acenaphthylene,
Acenaphthene, Fluorene, and Phenanthrene
components consistently exhibited the lowest
PAH availability and distribution, with
concentrations below 1.0 mg/L, and in several
instances, reaching undetectable The overall
concentration of PAHs reached its peak at SN 24
- FCLT 2 (4.899 mg/L), SN 5 - MKT 4 (4.862
mg/L), and SN 21 - SET 5 (4.56 mg/L). Notably,
SN 34 - SET 11 and SN 39 - SET 16 recorded
the lowest PAH concentrations, at 0.241 mg/L
and 0.324 mg/L, respectively.
Fig. 8 provides a clear visualization of the
distribution of Total Petroleum Hydrocarbon
(TPH) concentrations across all river and
rainwater samples collected from various
locations within the Oyigbo Local Government
Area. The figure distinctly portrays the varying
levels of TPH contaminations, showcasing a
hierarchical occurrence pattern. SN 26 (RVR 5)
emerges as the location with the highest TPH
concentration, recording 137.397 mg/L. In close
succession, SN 20 (MKT 7) follows with a
substantial TPH concentration of 128.179 mg/L.
Conversely, SN 36 (SET 13) registers the lowest
TPH concentration in the figure, indicating 8.976
mg/L.
This presentation effectively illustrates the
diverse distribution of petroleum hydrocarbon
contamination across the entire study area.
Additional samples with medium to high TPH
concentrations include SN 12 (RVR 3) at 76.676
mg/L, and SN 2 (MKT 1), SN 9 (FCLT 1), SN 19
(MKT 6), SN 23 (SET 7), ranging from 100 mg/L
to 70 mg/L. Samples showing average TPH
concentrations include SN 18 (RVR 4), SN 19
(MKT 6), SN 29 (SCH 4), SN 41 (RVR 7), SN 23
(SET 17), SN 24 (FCLT 2), with concentrations
ranging from 70 mg/L to 50 mg/L. Samples with
average to lower TPH concentrations include SN
14 (SCH 3), SN 32 (SET 10), SN 22 (SET 6)
ranging within 40 mg/L to 20 mg/L.
Samples displaying relatively lowest TPH
concentrations are SN 15 (SET 2), SN 30 (SET
8), SN 31 (SET 9) with concentrations ranging
from between 20 mg/L to 10 mg/L, and SN 36
(SET 13), SN 35 (SET 12), and SN 17
(SET 4) records the least TPH concentration at
8.976 mg/L, 9.613 mg/L, and 9.583 mg/L
respectively.

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Fig. 8. TPH Distribution Chart for Rain and River Water Samples across the Study Area
3.2 Total Petroleum Hydrocarbon (TPH)
Geospatial Variation
Fig. 9a to 9h illustrate the spatial variation maps
of the Aliphatic Hydrocarbon components across
the study area, Fig. 9i depicts the spatial
variation maps for Total Aliphatic Hydrocarbon
(TAH), and Polycyclic Aromatic Hydrocarbon
(PAH), while Fig. 9j shows the spatial variation of
the Total Petroleum Hydrocarbons (TPH). The
analysis of hydrocarbons with smaller chain
lengths (C8 to C17) consistently revealed low
concentrations, depicted by light coloration in the
mapped area. Conversely, long-chain
hydrocarbons from C18 to C40 and Pristane
displayed an even distribution across the study
area without distinct hotspots. Phytane, however,
exhibited higher concentrations in the western
part of the study area and lower values in the
eastern part (Fig. 9h). Spatial maps illustrated
significant variation, with lighter colors indicating
lower values in the southern parts and localized
hotspots indicating higher hydrocarbon
concentrations, particularly along the Imo River
channel in the northern part (Fig. 9i and 9j).
In assessing the geospatial variations of C6 to
C11 and C12 to C15 Aliphatic Hydrocarbon
components (Fig. 9a and 9b) across the study
area, heightened concentrations were identified,

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particularly in the western and central regions.
Notably, for C8 to C15 components, significant
concentrations were observed at specific
locations such as Imo River - Obiama and
Okoloma areas in the Komkom-Obiama, and
Okoloma axis respectively, Community
Secondary School, Umuakpahu and Obigbo
Market area in the Obigbo axis, and Umuosi
Market area in the Okoloma axis. The
concentration peaks in these areas, represented
by a darker color intensity on the map, signify
substantial pollution levels in the specified
locations. Conversely, lower variations in this
category were predominantly observed in the
eastern regions, particularly at Azuagu, Obete,
and Okpontu settlement areas, all situated in the
Umu Agbai-Obete axis, displaying lighter color
intensity on the map, and indicating
comparatively lower pollution levels in these
areas.
Within the C16 to C21 and C22 to C25 ranges,
as illustrated in Fig. 9c and 9d, a noticeable
intensification in concentration is prominently
observed in the northwestern and north-central
parts of the study area, depicted by the deep
coloration on the map. The mapping distinctly
reveals heightened pollution levels in key
locations, notably in the Umuosi area, Imo River,
Otamiri River, Komkom area, Umuebele area in
the Obigbo, Komkom-Obiama, and Okoloma
axes of the study. Conversely, the southern
region of the study area consistently displays
lower concentrations, evident from the lighter
color intensities, particularly in the Ban-Lori and
Ndoki areas within the Egberu and Umu Agbai-
Obete axes. The substantial variations between
these regions of high and low pollution intensity
underscore the significant disparities in
contamination levels.
Fig. 9a. Spatial variations of C8 to C11 Aliphatic Hydrocarbon contents across the Study Area

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Fig. 9b. Spatial variations of C12 to C15 Aliphatic Hydrocarbon contents across Study Area
In the context of C26 to C31 and C32 to C35
components, as depicted in Fig. 9e and 9f, the
spatial variation maps reveal heightened
pollution concentrations primarily in the northern
regions of the study area, consistently portrayed
by deep color intensities. The areas exhibiting
elevated pollution levels are predominantly in the
Umuosi area and Imo River area within the
Okoloma axis of the study. Additionally,
contaminated zones, as indicated by the spatial
variation map, include the Timber Market and
Atata Market areas, both situated in the Obigbo
axis. In contrast, a lesser intensity of
contamination is observed in the southern strip
and eastern regions of the study area,
particularly around the Obigbo-Etche
boundary regions, Umu Agbai, Egberu, and
Obete areas. The spatial distribution
underscores the close proximity of these high
pollution areas to the location of oil and gas
production facilities in the Obigbo and Okoloma
regions.
For C36 to C39 components (Fig. 9g), the spatial
variation map reveals a comparatively lower
contamination intensity of these components
compared to others across the entire study area.
There is a moderate dispersion and variation of
the C36 to C39 components, as indicated by
predominantly light-colored regions throughout
the study area. Specific location-bound hotspots
are observed at two points, with Umuosi, Imo
River, Timber Market, and Atata Market areas in
the Obigbo and Okoloma axis displaying higher
pollution levels. Overall, these components
exhibit a medium contamination intensity, as
suggested by the average color tone covering
the majority of the study area. The areas with the
lowest pollution are depicted by very light colors
on the map, primarily located at the Umu Agbai
and Obete axis of the study.

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Fig. 9c. Spatial variations of C16 to C21 Aliphatic Hydrocarbon contents across the Study Area

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Fig. 9d. Spatial variations of C22 to C25 Aliphatic Hydrocarbon contents across Study Area
In Fig. 9h, the geospatial variations for C40,
Pristane, and Phytane components of the
Aliphatic Hydrocarbons are depicted. Upon
examining C40 and Phytane concentrations, a
similar pollution dispersion pattern is observed,
evident in the color-coding style across the study
area. These components exhibit heightened
pollution in the North-central and North-western
regions, with medium pollution extending from
these zones towards the Southwestern to Central
parts. The peaks are primarily concentrated
around the Shell Flow Station, and Afam Power
Plant, in the Obigbo and Okoloma axis, indicating
a significant deposition of the heavier C40
components around the sources of
contamination. Conversely, lesser pollution
dispersion is observed around the Komkom, Ka
Lori, and Obete areas, while average pollution
dispersion is displayed in the Obiama and
Egberu areas. For Pristane, high pollution
concentrations are distributed across major
regions, illustrating a well-distributed
spatial variation throughout the study area
in the Obigbo, Komkom-Obiama,
Okoloma, Egberu, and parts of the Umu Agbai-
Obete axis.

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Fig. 9e. Spatial variations of C26 to C31 Aliphatic Hydrocarbon contents across the Study Area

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Fig. 9f. Spatial variations of C32 to C35 Aliphatic Hydrocarbon contents across the Study Area
In general, the Aliphatic Hydrocarbons registered
its heightened pollution levels at locations
including RVR 5, MKT 3, MKT 6, MKT 7, SET 7,
and SCH 2, corresponding to Imo River, Atata
Market, Okoloma Market, Umuosi Market, Afam
area, and Community Secondary School,
Umuakpahu, located in the Okoloma, Obiama,
and Obigbo study locations and axes.
Conversely, the least pollution intensities were
observed at SET 4, SET 8, SET 9, SET 12, SET
13, and SET 15, situated in Obiama Settlement
area, Afam-Uku Settlement areas, Egberu-Ndoki
Settlement area, Umu Agbai Settlement area,
Okpontu Settlement area, and Marihun
Settlement areas, within the Obiama, Egberu,
and Umu Agbai-Obete study axis.
The overall concentration of Polycyclic Aromatic
Hydrocarbons (PAH) prominently heightened in
the Northern, North-western, and South-central
locations, specifically at MKT 4, SCH 1, SET 5,
SET 6, MKT 6, and FCLT 2. Conversely, SET 3,
SET 8, SET 9, MKT 8, MKT 9, SET 11, SET 12,
and SET 16 recorded the lowest PAH
concentrations. These areas with lower pollution
levels are primarily situated in Komkom, Egberu,
Umu Agbai, and Obete, spanning the Western,
Central, and Eastern regions of the study area.

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25
Fig. 9g. Spatial variations of C36 to C39 Aliphatic Hydrocarbon contents across the Study Area
Overall, the Total Petroleum Hydrocarbon (TPH)
demonstrates its highest pollution dispersion in
the North-central and North-western regions of
the study area, with a generally medium
dispersion more prevalent across the Central and
Southern regions. The lowest pollution is
predominantly displayed in the Eastern regions,
evident in corresponding TPH concentrations
and differences in color intensities. Specifically,
the Umuosi, Obumku, and Imo River areas in the

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26
Okoloma axis, as well as the Umuebele areas in
the Obigbo axis, exhibit the highest pollution
levels, while the lowest pollution is observed at
Obiama Settlement areas in the Obiama region,
Egberu-Ndoki Settlement areas in the Egberu
axis, and Marihun and Okpontu Settlement
areas in the Umu Agbai-Obete axis of the study
area.
Fig. 9h. Spatial variation of C40, Pristane and Phytane Aliphatic Hydrocarbon across Study
Area

Ahmed et al.; J. Geo. Env. Earth Sci. Int., vol. 28, no. 3, pp. 1-30, 2024; Article no.JGEESI.113182
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Fig. 9i. Spatial Variation of Aliphatic Hydrocarbons and PAH across Study Area
Fig. 9j. Spatial Variation of Total Petroleum Hydrocarbon (TPH) across the Study Area

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4. CONCLUSION
This study provides a thorough examination of
Total Petroleum Hydrocarbon (TPH)
concentrations in rain and rivers affected by soot
contamination in Oyigbo, Rivers State, Niger
Delta, Nigeria. The research focuses on
understanding the geospatial variability and
distribution of TPH, with a specific emphasis on
Aliphatic Hydrocarbons and Polycyclic Aromatic
Hydrocarbons (PAHs), aiming to identify pollution
hotspots and vulnerable areas.
The investigation categorizes hydrocarbons
based on chain lengths and components,
revealing consistent concentrations of Lighter
Aliphatic Hydrocarbons at specific locations.
However, variations are observed in Medium and
Heavy Aliphatic Hydrocarbons, and distinct
patterns emerge in Pristane and Phytane
concentrations across locations. Out of the 41
samples, 19 locations exceeded the 50 mg/L
acceptable limits set by the World Health
Organization [32] and the Department of
Petroleum Resources [33]. Additionally, 10
locations recorded concentrations above, while
12 locations fell below 30 mg/L. These results
indicate that approximately 46% exhibited high,
24% displayed medium, and 29 % showcased
low concentrations across the study area. The
study highlights the highest pollution dispersion
in the North-central and North-western regions,
with medium dispersion more prevalent in the
Central and Southern regions. The Eastern
regions consistently display the lowest pollution
levels, particularly in Obiama, Egberu-Ndoki, and
Marihun-Okpontu Settlement areas. Conversely,
higher pollution levels are likely linked to
proximity to major petroleum production facilities
in the Okoloma and Obigbo axes.
Exposure to TPH in soot-contaminated rain and
river water poses potential human health risks,
including respiratory issues and skin irritations.
Additionally, consumption of contaminated water
can contribute to respiratory problems and
gastrointestinal disorders [34]. Ecologically, TPH
contamination disrupts aquatic ecosystems,
harming fish, invertebrates, and organisms
throughout the food chain [31]. Urgent
intervention is required through enhanced
monitoring, remediation efforts, and strict
regulatory measures. Sustainable water
management practices are crucial for minimizing
the impact of TPH contamination on human
health and ecosystems. The study's findings
contribute valuable insights for environmental
sustainability in Oyigbo, emphasizing the need
for a holistic approach to address hydrocarbon
contamination. Increased monitoring,
remediation, and regulatory efforts are necessary
to mitigate the impact on water resources and
surrounding ecosystems [35].
COMPETING INTERESTS
Authors have declared that no competing
interests exist.
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