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ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue XIII October 2025
Special Issue on Innovations in Environmental Science and Sustainable Engineering
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Impact of Population Growth on the Spatial Distribution of
Particulate Matter (Pm
2.5
) in the Niger Delta
Boyitie, Paul Odiyirin
1*
, Enamuotor, Oghenekevwe
2
, Ojjeh, Collins Oghenekome
3
1,2
Nigeria Maritime University, Okerenkoko, Delta State, Nigeria
3
Dennis Osadebay University, Asaba, Delta State, Nigeria
*Corresponding Author
DOI:
https://dx.doi.org/10.51584/IJRIAS.2025.101300004
Received: 02 October 2025; Accepted: 10 October 2025; Published: 06 November 2025
ABSTRACT
This study examines the impact of population growth on the spatial distribution of PM
2.5
in the Niger Delta,
integrating satellite and ground-based data to assess pollution trends. Findings reveal a steady increase in PM
2.5
concentrations from 308 PPM (1990–2004) to 532.5 PPM (2015–2024), with urban centres like Imo, Abia, and
Rivers experiencing the highest pollution levels due to rapid urbanization and industrial activities. A moderate
association (R = 0.570) between PM
2.5
concentrations and population increase are confirmed by regression
analysis. Significant differences in PM
2.5
pollution levels between states are highlighted by the study, with
more industrialised areas showing higher PM
2.5
levels than locations with less urbanisation and more
vegetation cover. The ANOVA results (F = 284.473, p < 0.000) indicate statistically significant differences in
pollution levels, necessitating targeted interventions. Stricter emissions controls, better industrial waste
management, and improved air quality monitoring systems are advised in order to reduce air pollution.
Strengthening urban planning policies to balance development with environmental sustainability is also
crucial. These measures are essential for safeguarding public health, as prolonged exposure to high PM
2.5
levels increases the risk of respiratory and cardiovascular diseases. The study highlights the need for proactive
environmental policies and sustainable urban growth strategies to improve air quality and overall well-being in
the Niger Delta.
Keywords: Urbanization, PM
2.5
, Population Growth, Air Pollution, Environmental Sustainability
INTRODUCTION
The rapid increase in global population has significantly affected both natural and urban ecosystems. Air
pollution, which offers major threats to public health, is one of the most important environmental issues linked
to this increase (Maji et al., 2023). The Niger Delta, known for its expanding population, industrialization, and
extensive crude oil extraction, has seen a sharp decline in air quality. Despite the severity of this issue, the
relationship between population growth and the spatial distribution of fine particulate matter (PM
2.5
) remains
insufficiently explored, necessitating a deeper investigation into how demographic shifts influence pollution
levels in this environmentally fragile region (Brida et al., 2024; Huang et al., 2024).
Urban expansion intensifies human activities, leading to increased pollution. Exposure to PM
2.5
has serious
health effects, especially in areas with lax environmental laws and insufficient air quality monitoring. Long-
term exposure to high pollution levels poses health dangers to people of the Niger Delta, where environmental
rules are not consistently enforced (Abulude et al., 2024). The World Health Organisation (WHO) states that
the average annual percentage of PM2.5 should not exceed 10 µg/m³ (2.3 PPM). The region's air quality is
greatly impacted by oil spills, gas flaring, and industrial pollutants, all of which are important effects of
petroleum extraction (Akinwumiju et al., 2020). Furthermore, the issue is made worse by uncontrolled
transportation networks, biomass burning, and inadequate waste management (Nwadiaro et al., 2019; Zhang et
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
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Special Issue on Innovations in Environmental Science and Sustainable Engineering
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al., 2024). Creating efficient pollution management plans for cities and their environs requires an
understanding of how these variables interact with population increase.
Research on PM
2.5
exposure's geographical distribution in connection to population expansion is still rare,
despite the well-established hazards to the environment and human health (Apte et al., 2018). According to
Guo et al. (2016), most studies have focused on industrial pollution, neglecting the ways that increasing
urbanisation, human settlements, and other anthropogenic activities raise PM
2.5
levels. This knowledge gap
hinders the formulation of targeted policies aimed at improving air quality and protecting public health
(Zambrano-Monserrate et al., 2024). This study intends to close the gap by examining how population growth
influences the spatial distribution of PM
2.5
in the Niger Delta. Examining these patterns will provide crucial
insights for public health policies, pollution mitigation measures, and sustainable urban planning. Analysing
pollution levels across different population densities will generate critical data to inform environmental
policies, helping to clarify the dynamics of air pollution in metropolitan areas that are expanding quickly and
highlighting the significance of sustainable development.
Conceptual Issues and Empirical issues/literature
Environmental degradation, driven by rapid population growth, urbanization, and industrial expansion,
remains a pressing concern in regions undergoing economic transformation. One of the most important effects
of these is declining air quality, which is shown by an increase in fine particulate matter (PM
2.5
) levels (Maji et
al., 2023). While extensive research has explored the environmental impacts of human activities, the
relationship between population growth and pollution levels requires further investigation. Air pollution, as a
dimension of environmental degradation, has well-documented links to human health and urbanization (Gul &
Das, 2023; Murano et al., 2023). Exposure to PM
2.5
is associated with respiratory diseases, cardiovascular
conditions, and reduced life expectancy (Pryor et al., 2022). In the Niger Delta, rapid urban expansion has led
to increased vehicular emissions, biomass combustion, and industrial discharges, exacerbating health risks
(Numbery, 2020). The lack of effective pollution control measures has further intensified public health
challenges, making air quality deterioration a critical issue (Ramayah et al., 2019).
Despite theoretical advancements in environmental studies, gaps remain in understanding the direct link
between population growth and PM
2.5
distribution. While industrial pollution has been widely documented, the
role of urbanization, migration, and human activities in shaping particulate matter concentrations is less
explored. Addressing this gap is essential for formulating targeted policies that balance economic growth with
environmental sustainability. This study builds on existing environmental degradation frameworks to
investigate the impact of population expansion on the spatial distribution of PM
2.5
. By integrating ecological
theories with spatial analysis techniques, it seeks to provide a comprehensive understanding of pollution trends
in the region. To lessen the negative consequences of population-driven pollution, the results will highlight the
necessity of stricter environmental regulations, improved air quality monitoring, and sustainable urban
development.
MATERIALS AND METHODS
One of Nigeria's most resource-rich and ecologically delicate areas is the Niger Delta in the south of the
country (Nwankwoala & Okujagu, 2021). Comprising nine states, including Rivers, Delta, Bayelsa, and Akwa
Ibom, it has a population of over 50 million and occupies an area of roughly 70,000 square kilometres (Nwilo
& Badejo, 2006; Boyitie et al., 2024). The Niger Delta lies between latitude 3˚00'N and 6˚00'N and longitude
5˚00'E and 8˚00'E (see Figure 1). Its varied ecosystems sustain industrial, agricultural, and fishing endeavours,
all of which exacerbate environmental problems and economic growth. Air quality has significantly declined
as a result of petrol flaring, oil spills, and industrial emissions; PM
2.5
pollution is becoming a serious public
health problem (Olalekan et al., 2021). Major cities such as Port Harcourt, Warri, and Yenagoa have
experienced significant population surges due to rural-urban migration and economic opportunities linked to
the oil sector (Adibe & Ohochuku, 2022).
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Figure 1: Map of the Niger Delta Cartographic Unit of the Department Urban and Regional Planning Dennis
Osadebay University, Asaba
The study uses an ex post facto research approach to investigate the connection between PM
2.5
geographical
distribution and population increase. By integrating quantitative analysis with qualitative insights, it provides a
comprehensive assessment of air pollution dynamics in the Niger Delta. The study focuses on nine major
urban and industrial centres where population expansion and environmental concerns are most pronounced
(see Table 1). A preliminary reconnaissance visit identified key locations for on-site air quality measurements,
ensuring representative sampling across the study area.
Table 1: Sampling Areas
Sample States
Sample Areas
Coordinates of Sample locations
Abia
Aba
5°06'56.8"N 7°22'19.9"E
Akwa Ibom
Uyo
4°40'08.5"N 7°57'04.2"E
Bayelsa
Yenagoa
4°57'17.0"N 6°21'49.5"E
Cross Rivers
Calabar
4°58'17.5"N 8°20'21.0"E
Delta
Warri
5°32'44.7"N 5°46'46.3"E
Edo
Benin
6°20'03.7"N 5°37'19.9"E
Imo
Owerri
5°27'27.6"N 7°02'27.6"E
Ondo
Akure
7°15'08.0"N 5°11'09.6"E
Rivers
Port Harcourt
4°49'12.3"N 6°58'34.7"E
Fieldwork, 2024
Both ground-based air quality monitoring stations and satellite-based remote sensing provided the data on
PM
2.5
concentrations. NASA's Earth Observing System satellite data was included in the study because of its
accessibility and worldwide coverage. The Terra and Aqua satellites' MODIS sensor, which has 36 spectral
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channels, provided the data. Collection 9 Terra MODIS data, which were taken every day at five-minute
intervals, were used to derive Aerosol Optical Depth (AOD) values, which show light extinction by
atmospheric particles. Monthly and yearly means were calculated by averaging these numbers. The satellite
data span nearly three decades (1995–2024), offering a long-term perspective on pollution trends. Ground-
based measurements were conducted biweekly in February and July 2024 using an open-air sampling method
with Sage thermal mass flow meters. These devices recorded PM
2.5
concentrations in all nine selected
locations, providing localized data to validate satellite observations. A thorough evaluation of pollution levels
and regional variations is ensured by the integration of various sources. Population data were obtained from
demographic databases and the Nigerian National Population Commission, enabling an analysis of population
density fluctuations over time. To determine empirical regional differences in PM
2.5
, correlations between
population growth and PM
2.5
concentrations, and projected trends in PM
2.5
, statistical approaches such as
ANOVA, regression analysis, and time series analysis were used. Secondary data from environmental reports,
government records, and previous studies provided additional context and validation. This methodological
approach ensures a reliable and well-contextualized examination of how demographic trends influence air
quality. The findings will contribute to the development of targeted policies aimed at mitigating pollution and
improving environmental management in the Niger Delta.
RESULTS AND DISCUSSION
Table 2: Niger Delta States' Average Population and Population Growth Rates (2006–2024)
States
Growth Rate
Abia
2.7
Akwa Ibom
3.4
Bayelsa
2.9
Cross Rivers
2.9
Delta
3.2
Edo
2.7
Imo
3.2
Ondo
3
Rivers
3.4
Source: Population Gazette of National Bureau of Statistics
Table 2 presents the population growth rates and average population for nine states in the Niger Delta,
reflecting demographic trends that influence environmental changes, including air quality. The region's
population has grown significantly, according to the data, with growth rates ranging from 2.7% to 3.4%. The
biggest growth rates (3.4%) are found in Rivers and Akwa Ibom, suggesting that these areas are rapidly
becoming more urbanised and populated, which may lead to rising pollution levels. In terms of absolute
population, Rivers State leads with an average population of 7,182,817, followed by Delta (5,569,641) and
Akwa Ibom (5,391,277). The lowest population is recorded in Bayelsa (2,240,869), which, despite its
resource-rich environment, has a relatively smaller population due to its extensive water bodies and difficult
terrain. These demographic trends are crucial in assessing the impact of population growth on PM
2.5
distribution (Liyanage & Yamada, 2017).
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Figure 2: Niger Delta Population Density by State
Figure 2 shows population density variations across Niger Delta states, with Edo, Ondo, and Bayelsa having
the highest density. These differences may be attributed to factors like urbanization, industrial activities, and
economic opportunities. Edo and Ondo are known for their growing urban centres, which attract migration and
increase population density. Lower densities may have more dispersed settlements or less industrial activity.
The results highlight how crucial it is to take population distribution into account when planning infrastructure
and the environment, especially when it comes to air pollution levels. It is essential to comprehend these trends
in order to create strategies for environmental preservation and sustainable urban expansion.
Table 3: Mean Decadal PM
2.5
Concentrations Across States in the Niger Delta (1990–2024)
Mean Decadal PM
2.5
Concentrations in Part Per Million (PPM) Across States
States
1990-2004
2005-2014
2015-2024
Abia
499
683.1
854.6
Akwa
Ibom
438.8
605.2
788.8
Bayelsa
132.8
180.7
225.1
Cross
Rivers
115.6
153
189
Delta
203.8
282.8
359.2
Edo
148.5
191.4
238
Imo
582.7
785.9
967.3
Ondo
179.6
233.8
287.6
Rivers
471.5
688.1
882.9
Mean
308
422.7
532.5
Source: NASA’s Earth Observing System
1.32
1.27
1.35
1.33
1.25
1.34
1.21
1.35
1.21
1.10
1.15
1.20
1.25
1.30
1.35
1.40
Abia Akwa
Ibom
Bayelsa Cross
Rivers
Delta Edo Imo Ondo Rivers
Population Desnsity
States
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The mean decadal concentrations of fine particulate matter (PM
2.5
) in the Niger Delta from 1990 to 2024 show
a consistent upward trend, rising from 308 PPM (1990–2004) to 532.5 PPM (2015–2024). Imo, Abia, and
Rivers recorded the highest PM
2.5
levels, possibly due to rapid urbanization, industrial emissions, and
increased vehicular activities. Bayelsa and Cross Rivers had the lowest concentrations, likely due to lower
industrial activities and more extensive vegetation cover as opined by Nwosisi et al. (2021).
Table 4: PM
2.5
Levels in a Selection of Cities in 2024
PM
2.5
Concentration in PPM
Aba
Uyo
Yenagoa
Calabar
Warri
Benin
Owerri
Akure
Port
Harcourt
Average
PM
2.5
3.55
4.47
5.43
5.35
4.67
4.16
3.80
3.53
4.83
Source: Field Data, 2024
Table 4 presents the average PM
2.5
concentration (in parts per million) across nine cities: Aba, Uyo, Yenagoa,
Calabar, Warri, Benin, Owerri, Akure, and Port Harcourt. The highest concentration is recorded in Yenagoa
(5.43 PPM), closely followed by Calabar (5.35 PPM) and Port Harcourt (4.83 PPM). These values indicate
relatively higher air pollution levels in these locations, likely due to industrial activities, vehicular emissions,
or other anthropogenic factors as opined by Yu et al. (2024). Conversely, Akure (3.53 PPM) and Aba (3.55
PPM) report the lowest concentrations, suggesting comparatively cleaner air. The variations in PM
2.5
levels
across the cities may be influenced by differences in population density, industrial presence, and
meteorological conditions as opined by Afifa et al. (2024). Monitoring and controlling PM
2.5
pollution are
essential for public health, as prolonged exposure to elevated levels can lead to respiratory and cardiovascular
complications.
Table 5: ANOVA Results for PM
2.5
Emission
Sum of Squares
df
Mean Square
F
Sig.
Between Groups
10844044.934
8
1355505.617
284.473
.000
Within Groups
643270.713
135
4764.968
Total
11487315.646
143
Source: SPSS Computed
The ANOVA results in this table 5 examine the differences in PM
2.5
emissions across various states in the
Niger Delta. The F-value of 284.473 and the p-value of 0.000 indicate a statistically significant difference in
PM
2.5
emissions between the groups. This variation is largely due to differences in industrialization, population
density, and regulatory enforcement. Intra-state variations are less pronounced, indicating a need for state-
specific policy interventions. High-pollution areas may require stricter emissions controls, improved air quality
monitoring, and targeted mitigation strategies to effectively address environmental and public health concerns.
Table 6: Multiple Comparisons of PM
2.5
Emissions Across States
Tukey HSD
(I) State
(J) States
Mean
Difference
(I-J)
Std.
Error
Sig.
95% Confidence Interval
Lower
Bound
Upper
Bound
1 Abia
3 Bayelsa
557.86250
*
24.405
35
.000
480.9183
634.8067
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4 Cross
Rivers
589.15625
*
24.405
35
.000
512.2120
666.1005
5 Delta
441.57500
*
24.405
35
.000
364.6308
518.5192
6 Edo
546.26875
*
24.405
35
.000
469.3245
623.2130
7 Imo
-
108.56875
*
24.405
35
.001
-185.5130
-31.6245
8 Ondo
500.48125
*
24.405
35
.000
423.5370
577.4255
2 Akwa
Ibom
3 Bayelsa
485.58750
*
24.405
35
.000
408.6433
562.5317
4 Cross
Rivers
516.88125
*
24.405
35
.000
439.9370
593.8255
5 Delta
369.30000
*
24.405
35
.000
292.3558
446.2442
6 Edo
473.99375
*
24.405
35
.000
397.0495
550.9380
7 Imo
-
180.84375
*
24.405
35
.000
-257.7880
-103.8995
8 Ondo
428.20625
*
24.405
35
.000
351.2620
505.1505
9 Rivers
-87.68125
*
24.405
35
.013
-164.6255
-10.7370
3 Bayelsa
5 Delta
-
116.28750
*
24.405
35
.000
-193.2317
-39.3433
7 Imo
-
666.43125
*
24.405
35
.000
-743.3755
-589.4870
9 Rivers
-
573.26875
*
24.405
35
.000
-650.2130
-496.3245
4 Cross
Rivers
5 Delta
-
147.58125
*
24.405
35
.000
-224.5255
-70.6370
7 Imo
-
697.72500
*
24.405
35
.000
-774.6692
-620.7808
8 Ondo
-88.67500
*
24.405
35
.012
-165.6192
-11.7308
9 Rivers
-
604.56250
*
24.405
35
.000
-681.5067
-527.6183
5 Delta
6 Edo
104.69375
*
24.405
35
.001
27.7495
181.6380
7 Imo
-
550.14375
*
24.405
35
.000
-627.0880
-473.1995
9 Rivers
-
456.98125
*
24.405
35
.000
-533.9255
-380.0370
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6 Edo
7 Imo
-
654.83750
*
24.405
35
.000
-731.7817
-577.8933
9 Rivers
-
561.67500
*
24.405
35
.000
-638.6192
-484.7308
7 Imo
8 Ondo
609.05000
*
24.405
35
.000
532.1058
685.9942
9 Rivers
93.16250
*
24.405
35
.006
16.2183
170.1067
8 Ondo
9 Rivers
-
515.88750
*
24.405
35
.000
-592.8317
-438.9433
*. The mean difference is significant at the 0.05 level.
Source: SPSS Computed
Table 6 compares PM
2.5
emission levels between states in the Niger Delta, revealing significant disparities in
air pollution levels. In comparison to Bayelsa, Cross Rivers, and Rivers, states such as Abia, Akwa Ibom,
Delta, and Edo have much greater PM
2.5
emissions. Compared to Bayelsa, Cross Rivers, and Delta, Abia and
Akwa Ibom have much greater emissions. Conversely, states with lower PM
2.5
emissions, such as Bayelsa and
Cross Rivers, show significantly lower values compared to high-pollution states like Imo and Rivers. There are
notable differences in the air quality across Bayelsa, Imo, and Rivers; the PM
2.5
levels in Cross Rivers are
lower. Rivers has greater PM
2.5
levels than Imo, the most polluted state, suggesting that industrialisation and
urbanisation may be contributing factors to the latter's high pollution levels. The necessity for specific
environmental policies and regulatory actions to address air pollution inequalities in the Niger Delta is
highlighted by the statistical significance of these comparisons (p <0.05), which demonstrates that observed
discrepancies in PM
2.5
levels are unlikely to be the result of chance.
Table 7: Population Density and Average PM
2.5
Concentrations in the Niger Delta
States
Population Density
Average PM
2.5
(PPM)
Abia
1.32
758.3
Akwa Ibom
1.27
686
Bayelsa
1.35
200.4
Cross Rivers
1.33
169.1
Delta
1.25
316.7
Edo
1.34
212
Imo
1.21
866.8
Ondo
1.35
257.8
Rivers
1.21
773.7
Average
1.29
471.18
Source: Population Gazette of National Bureau of Statistics and NASA’s Earth Observing System
Table 7 reveal a general pattern where states with higher population density tend to exhibit elevated PM
2.5
levels, though some variations exist. Imo and Rivers, which have the lowest population densities (1.21),
recorded some of the highest PM
2.5
levels (866.8 PPM and 773.7 PPM, respectively). This suggests that factors
beyond population density, such as industrial activity and transportation emissions, significantly contribute to
air pollution (Afifa et al., 2024). Similarly, Abia (1.32) and Akwa Ibom (1.27) also recorded high PM
2.5
levels,
supporting the link between urbanization and air quality deterioration. Conversely, Bayelsa and Cross Rivers,
despite having relatively high population densities (1.35 and 1.33, respectively), reported much lower PM
2.5
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concentrations (200.4 PPM and 169.1 PPM, respectively). This could be attributed to lower industrialization,
better environmental policies, or greater forest cover mitigating pollution levels (Rafaj et al., 2018). On
average, the region's PM
2.5
concentration stands at 471.18 PPM, which significantly exceeds global air quality
standards, posing serious health risks. The findings reinforce the need for effective pollution control measures,
sustainable urban development, and improved air quality monitoring to address the rising environmental
concerns in the Niger Delta.
Table 8: Regression on the Relationship between Population and PM
2.5
Concentrations
Mo
del
R
R
Squa
re
Adjuste
d R
Square
Std.
Error of
the
Estimat
e
Change Statistics
R
Square
Change
F
Chan
ge
df1
df2
Sig. F
Change
1
.5
70
a
.325
.321
233.621
00
.325
68.47
2
1
142
.000
a. Predictors: (Constant), Population in Niger Delta
Sources: SPSS Computed
The statistical correlation between Niger Delta PM
2.5
values and population increase are seen in Table 8.
According to the R value (0.570), there is a slightly positive association between population size and air
pollution levels, indicating that PM
2.5
concentrations tend to rise along with population growth. The R Square
value (0.325) signifies that 32.5% of the variance in PM
2.5
levels is explained by population growth, while the
Adjusted R Square (0.321) accounts for potential overfitting, maintaining a stable explanatory power.
Population significantly impacts air pollution levels, but other factors like industrial emissions, land-use
changes, and regulatory effectiveness may also contribute (Shaddick et al., 2020). This is supported by the F-
statistic, however 67.5% of unexplained variation points to the need for more study.
Figure 3 shows the predicted PM
2.5
trends for the states of Abia, Akwa Ibom, Bayelsa, Cross Rivers, Delta,
and Edo between 1990 and 2034
Source: SPSS Output
Over the next ten years, the emissions prediction for the Niger Delta indicates a change in patterns (see Figures
3 and 4). Akwa Ibom is anticipated to progressively drop from 818.09 in 2025 to 801.96 in 2034, whereas
Abia is predicted to rise steadily from 904.68 in 2025 to 1109.52 by 2034. Bayelsa remains stable, with a slight
increase from 232.79 to 238.38. Cross Rivers follows a similar pattern, increasing from 194.70 to 202.13.
Delta's forecast shows a slow decline, starting at 371.47 in 2025 and dropping to 361.69 by 2034. Edo steadily
increases from 249.74 to 303.41, suggesting a gradual but predictable rise in emissions over time. Imo
experiences a slow decline, going from 993.47 in 2025 to 956.11 by 2034. Ondo stays almost flat, with
emissions barely shifting from 293.74 to 291.70 over the decade (see Figure 4). Rivers stands out with a strong
upward trajectory, increasing from 950.18 in 2025 to 1227.83 in 2034. The confidence intervals widen
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
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Special Issue on Innovations in Environmental Science and Sustainable Engineering
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significantly, suggesting potential for even higher emissions than predicted. Overall, the trends indicate that
since every region has unique patterns, state-specific initiatives to regulate emissions will be required.
Figure 4: Forecast trend of PM2.5 of Imo, Ondo and Rivers States from 1990 to 2034
Source: SPSS Output
Between 2006 and 2024, the population of the Niger Delta increased dramatically, with Rivers State having the
largest average population (7,182,817). In high-growth regions, rapid urbanisation exacerbates environmental
issues like air pollution. Increased human activity is correlated with the population density in metropolitan
regions like as Edo and Ondo, which may exacerbate pollution. Increased density frequently results in more
emissions from industry and automobiles, which affects public health and air quality. Over the course of three
decades, PM
2.5
levels have gradually climbed throughout the Niger Delta, with Imo continuously registering
the highest levels, followed by Abia and Rivers. Bayelsa and Cross Rivers had the lowest concentrations,
attributed to lower industrial activity and higher vegetation cover. ANOVA results demonstrate statistically
significant disparities in emissions among states, necessitating state-specific policies rather than broad
interventions. Multiple comparison analysis further reveals significant disparities in PM
2.5
emissions between
high-pollution states such as Imo and Rivers and lower-emission states like Bayelsa and Cross Rivers. A
moderate positive correlation (R = 0.570) between population growth and PM
2.5
concentrations is established,
with 32.5% of pollution variance attributed to population increase. However, additional elements like land-use
changes and industrial emissions also have a role, calling for more comprehensive policy considerations.
CONCLUSION
The results demonstrate a strong correlation between rising PM
2.5
levels and population growth throughout the
Niger Delta, with the greatest pollution levels seen in states that are rapidly urbanising and expanding
industrially. Significant environmental and public health issues are raised by the most severe air quality
degradation, which is often reported in Imo, Rivers, and Abia. Given the significant variance in pollution
levels across states, a uniform approach to air quality management may be ineffective. Instead, targeted
interventions, such as stricter emissions regulations in high-pollution areas and improved environmental
policies in rapidly urbanizing states, are essential (Izah et al., 2024). To address the growing air pollution
crisis, policymakers should prioritize sustainable urban planning, enforce stricter industrial and emissions
controls. Long-term environmental and health concerns can be reduced with the support of green infrastructure
investments and public awareness campaigns about pollution reduction techniques. Future studies should
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue XIII October 2025
Special Issue on Innovations in Environmental Science and Sustainable Engineering
Page 56
www.rsisinternational.org
explore the impact of specific pollution sources, such as industrial activities and transportation, on PM
2.5
concentrations. Further understanding of seasonal fluctuations and long-term patterns may also be possible by
including meteorological data into pollution models. A comparative analysis of mitigation strategies in other
regions facing similar challenges may also offer valuable solutions for improving air quality in the Niger
Delta.
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