Urbanization and Air Pollution Dynamics in Port Harcourt

TITLE:  Urbanization and Air Pollution Dynamics in Port Harcourt

AUTHOR: ATANDA PRECIOUS MARY

INTRODUCTION

Port Harcourt, a major industrial city in southern Nigeria, is characterized by rapid urbanization and intense industrial activities, particularly from oil and gas operations. Over the years, this growth has led to significant land cover changes, especially an increase in built-up areas. Simultaneously, the city has experienced rising levels of air pollution, largely from vehicular emissions, industrial discharge, and gas flaring. Aerosols, which include fine particulate matter and harmful gases, are a key component of this pollution, posing serious health and environmental challenges.

The Normalized Difference Built-up Index (NDBI), derived from satellite imagery, is a widely used metric to quantify the extent and density of built-up areas, reflecting urban development patterns. Aerosol levels, measured as Aerosol Optical Depth (AOD), indicate the concentration of particulate matter in the atmosphere, which can affect air quality, climate, and public health. Understanding the interplay between urban growth (via NDBI) and aerosol levels in Port Harcourt provides insights into how human activities shape environmental conditions in this critical region.

Problem Statement

Rapid urbanization in Port Harcourt has led to increased impervious surfaces and industrial emissions, potentially elevating aerosol concentrations in the atmosphere. However, the specific relationship between the expansion of built-up areas, as captured by NDBI, and changes in aerosol levels remains underexplored in this context. This study investigates whether the growth of built-up areas correlates with higher aerosol levels, addressing a gap in localized environmental research amidst the city’s unique socio-economic and ecological setting.

Methodology

Data Collection Methods

This study relies entirely on secondary satellite data to ensure objectivity and scalability. It employs remote sensing and GIS techniques to analyze the relationship between urban expansion, vegetation cover, and aerosol concentration in Port Harcourt from 2019 to 2024. Data was sourced from three key satellite platforms:

Sentinel-2 – Used to compute:

• The Normalized Difference Built-up Index (NDBI) for identifying and monitoring built-up areas.
• The Normalized Difference Vegetation Index (NDVI) for assessing vegetation health and density across the study area.
• Sentinel-5P – Used to obtain aerosol concentration data, particularly the Aerosol Index (AI), which provides a quantitative measure of atmospheric aerosol presence.

These datasets were accessed and processed using Google Earth Engine (GEE), a cloud-based platform suitable for scalable and reproducible geospatial data analysis.

Tools and Techniques Used for Analysis

1. Google Earth Engine (GEE)

• Data Extraction: Sentinel-2 imagery was filtered by date and cloud cover to obtain annual dry-season composites from 2019 to 2024, ensuring minimal atmospheric interference.
• NDBI Calculation: NDBI = SWIR – NIR / SWIR+NIR​

SWIR (Shortwave Infrared) corresponds to Band 11 and NIR (Near Infrared) to Band 8 of Sentinel-2.

• NDVI Calculation: NDVI = NIR – RED/NIR+RED

Where NIR is Band 8 and RED is Band 4 of Sentinel-2. NDVI was chosen for its robustness in indicating vegetation vigor and potential for air quality regulation.

• Aerosol Data: Aerosol Index (AI) values were extracted from the COPERNICUS/S5P/OFFL/L3_AER_AI Annual mean AI was computed to represent each year from 2019 to 2024.

2. ArcGIS Pro

• Map Design and Visualization: Processed NDVI, NDBI, and aerosol rasters from GEE were exported into ArcGIS Pro for professional cartographic visualization.
• Spatial Analysis: NDVI and NDBI maps were classified to show vegetation health and urban expansion, respectively. Aerosol concentration maps were similarly symbolized to highlight pollution hotspots.
• Point Sampling & Value Extraction: A grid of representative sample points was generated across the study area. Using the “Extract Multi-Values to Points” tool, the aerosol, NDBI, and NDVI values were extracted for each point. This allowed spatially matched correlation analysis by compiling co-located values for each variable. The extracted point data, containing all three variables, was exported as a table for statistical analysis.

3. Microsoft Excel

• Charting and Statistical Analysis: Annual mean values of NDVI, NDBI, and aerosol index were compiled for trend visualization using line and bar charts.
• Correlation Analysis: Pearson correlation coefficients were computed to assess:
• The relationship between built-up expansion (NDBI) and aerosol concentration.
• The relationship between vegetation cover (NDVI) and aerosol concentration.

INTERPRETATION OF RESULTS

Urban Growth

The trend reveals a non-linear growth pattern, with significant fluctuations in the mean NDBI values over the six-year period.

Fig 2: Line chart showing mean NDBI

The NDBI trend reveals a dynamic pattern of urban growth in Port Harcourt over the study period. From 2019 to 2021, the mean NDBI decreased from 0.0282 to 0.0132, a decline of approximately 53%. This initial drop may reflect a slowdown in urban expansion, potentially influenced by global events such as the COVID-19 pandemic, which began in 2020 and led to economic disruptions, including reduced construction activities and migration to urban centers like Port Harcourt. However, a sharp reversal occurs from 2021 onward, with NDBI rising steadily to 0.0192 in 2022, 0.0457 in 2023, and slightly dipping to 0.0405 in 2024. The increase from 2021 to 2023—a 245% surge—signals a robust resurgence in urban development, likely driven by post-pandemic economic recovery, renewed oil sector investments, and population growth. The slight decline in 2024 (11% from 2023) might indicate a stabilization of urban expansion or a shift in development patterns, possibly due to land scarcity in the urban core or policy interventions.

The overall upward trajectory from 2021 to 2024 aligns with Port Harcourt’s socio-economic context, where rapid population growth (4–5% annually) and economic migration fuel demand for housing and infrastructure. The peak NDBI in 2023 (0.0457) suggests a high point of built-up intensity, potentially linked to major infrastructural projects or informal settlement expansion, which constitutes over 70% of the city’s growth.

These changes are further emphasized in the accompanying multi-temporal NDBI maps, which show the spatial footprint of built-up areas expanding progressively outward from the urban core into peri-urban and rural fringe zones.

Fig 3: NDBI Map

The NDBI trends in Port Harcourt bear resemblance to patterns observed in other rapidly urbanizing cities in the Global South. For instance, a study in Lagos, Nigeria (Oladunjoye et al., 2022, Remote Sensing Applications), reported a similar NDBI increase from 0.015 to 0.042 between 2018 and 2022, driven by population growth and commercial development. However, Lagos exhibited a more consistent upward trend without the initial decline seen in Port Harcourt, likely due to its larger economic base and less dependence on oil-related disruptions.

Air pollution Trends (2019–2024)

Aerosol levels in Port Harcourt were assessed using Aerosol Optical Depth (AOD) data derived from Sentinel-5P satellite imagery, with annual mean values calculated for the period from 2019 to 2024.

Fig 4: Line chart showing mean Aerosol Index

These values (Fig 3) indicate the concentration of aerosols in the atmosphere, with higher AOD reflecting greater particulate matter presence, often associated with pollution sources such as industrial emissions, vehicular exhaust, and dust.

The AOD trend over the study period exhibits significant variability, reflecting the complex interplay of natural and anthropogenic factors influencing air quality in Port Harcourt. From 2019 to 2021, mean AOD increased sharply from 0.6096 to 1.0068, a rise of approximately 65%. This peak in 2021 suggests a substantial deterioration in air quality, potentially linked to heightened industrial activity, increased illegal refining (noted in regional reports around this time), or seasonal factors like reduced rainfall during the dry season, which limits aerosol dispersion. The 2020–2021 period also coincides with the global COVID-19 pandemic, but unlike the NDBI decline observed during this time, AOD rose, possibly due to continued oil-related activities and informal sector emissions (e.g., biomass burning) despite reduced urban construction.

A notable decline in AOD occurs from 2021 to 2023, dropping from 1.0068 to 0.5322—a decrease of 47%. This improvement in air quality aligns with potential regulatory actions following public outcry over the black soot crisis, which persisted into the early 2020s, as well as possible meteorological shifts, such as stronger wet-season rainfall in 2022 and 2023, which can wash out aerosols. However, AOD rises again in 2024 to 0.7478, a 40% increase from 2023, indicating a resurgence of aerosol levels. This uptick may reflect renewed urban activity, as seen in the NDBI trends, or seasonal factors like dry-season stagnation, which traps pollutants.

Overall Correlation Result

The Pearson correlation coefficient was:

r = 0.015956

Table 1: Correlation coefficient (NDBI VS AEROSOL)

This result indicates an extremely weak and statistically insignificant positive correlation between built-up density (as indicated by NDBI) and aerosol concentrations over the study period. This weak correlation highlights a key insight: Urban expansion, as measured by surface-level built-up intensity, does not exhibit a strong or consistent linear relationship with aerosol pollution in Port Harcourt.

This analysis reveals that while urban expansion in Port Harcourt has a slight positive association with aerosol levels over the study period, the relationship is weak and heavily moderated by external factors. These findings provide a critical foundation for the recommendations to follow, emphasizing the need for a multi-faceted approach to air quality management in the region.

Mitigating Air Pollution – Relationship between NDVI and Aerosol levels

To evaluate whether vegetation cover plays a role in mitigating air pollution in Port Harcourt, the Pearson correlation coefficients between NDVI and aerosol concentrations were computed on a yearly basis, along with the average NDVI values. NDVI serves as an indicator of vegetation health and density, with higher values generally representing greener and more vegetated areas.

The overall Pearson correlation coefficient computed across the entire study period (2019–2024) was r = -0.241. This value reflects a moderate negative relationship between NDVI and aerosol concentrations across the study area. In practical terms, this means that areas with higher vegetation cover (as indicated by NDVI) generally experienced lower aerosol concentrations.

Table 4: Correlation coefficient (NDVI VS AEROSOL)

This inverse relationship suggests that vegetation may play a meaningful role in mitigating air pollution in Port Harcourt, though its influence is moderated by the dominant industrial emissions in the region.

In Port Harcourt, where oil refining, gas flaring, and vehicular emissions dominate air pollution profiles, the role of vegetation might be secondary but not negligible. The negative correlation implies that urban afforestation and greenbelt restoration could offer localized air quality improvements, particularly in residential and peri-urban areas less affected by industrial plumes. This result strengthens the argument for a multi-dimensional approach to air quality management in the city, combining regulatory controls on emissions with environmental strategies like tree planting and landscape planning.

Summary

This study examined the relationship between urban expansion and aerosol concentration in Port Harcourt, Nigeria, between 2019 and 2024, using satellite-derived indicators: the Normalized Difference Built-up Index (NDBI) for urbanization, and the Aerosol Index (AI) from Sentinel-5P to represent aerosol levels. Additionally, the Normalized Difference Vegetation Index (NDVI) was included to assess vegetation cover trends and their linkage to air quality.

Findings revealed a weak overall correlation between NDBI and aerosol levels (r = 0.02), indicating that urban growth alone does not significantly account for aerosol pollution in the city. However, localized or temporal peaks in correlation (e.g., in 2023) suggest that under certain conditions such as rapid, unregulated development, urbanization can exacerbate air quality issues.

The correlation between NDVI and aerosol index was moderately negative (r = -0.24), implying that areas with higher vegetation cover tend to experience lower aerosol concentrations. This affirms the protective role of vegetation in air quality regulation, as vegetation helps filter airborne pollutants, reduce surface temperatures, and improve urban microclimates.

Collectively, these insights highlight a multifactorial pollution dynamic in Port Harcourt, shaped not only by land use changes but also by industrial emissions, informal refining, seasonal factors, and vegetation loss. The study reinforces the need for an integrated environmental management approach that addresses both land development and ecological resilience.

Recommendations

Given the weak overall correlation between NDBI and AOD, air quality management in Port Harcourt should adopt a multi-pronged approach that addresses both urban growth and dominant pollution sources. The following recommendations are proposed:

Strengthen Regulation of Industrial and Informal Emissions: The significant AOD peak in 2021 (1.0068) and historical pollution events like the 2016 black soot crisis point to oil-related activities, particularly illegal refining, as major aerosol contributors. The Rivers State Government, in collaboration with the Federal Ministry of Environment, should intensify enforcement against illegal refineries, which cost Nigeria N30–60 trillion annually and contribute to soot emissions. Implementing stricter monitoring of gas flaring by oil companies like Shell and TotalEnergies, alongside adopting cleaner technologies, can further reduce industrial emissions.

Integrate Air Quality into Urban Planning: While the NDBI-AOD correlation is weak, the 245% NDBI increase from 2021 to 2023 highlights rapid urban expansion, particularly in informal settlements. Local authorities should prioritize sustainable urban planning by incorporating green spaces, enforcing zoning regulations, and improving infrastructure in informal areas to reduce dust and vehicular emissions. For example, paving roads in high-growth zones can minimize construction-related dust, a known aerosol source.

Enhance Air Quality Monitoring and Public Awareness: The study’s findings of high AOD levels (e.g., 1.0068 in 2021) underscore the public health risks of air pollution. Establishing a network of ground-based air quality monitoring stations across Port Harcourt, supported by NGOs like CEHRD, can provide real-time data to validate satellite observations and inform residents. Public awareness campaigns, building on movements like #StopTheSoot, should educate communities about pollution sources and protective measures, particularly in vulnerable areas.

Promote Regional Collaboration: Aerosol levels are influenced by transboundary factors, such as Saharan dust and regional industrial emissions. Port Harcourt authorities should collaborate with neighboring states and international bodies like UNEP to develop a regional air quality management framework, sharing data and strategies to address shared pollution challenges.