Monitoring Carbon Monoxide and Aerosol Concentrations in Aba Metropolis, Abia State, Nigeria: 2019–2024 Trends

Background: Air pollution poses major health and environmental risks globally, with disproportionate impacts in low- and middle-income countries lacking robust monitoring systems. In Nigeria, rapid urbanization, fossil fuel dependence, and informal industrial activities have intensified urban air quality challenges. In Aba, limited continuous, pollutant-specific monitoring has constrained comprehensive understanding of long-term temporal and spatial pollution dynamics. Objectives: This study quantified tropospheric carbon monoxide (CO) and aerosol concentrations in Aba (2019–2024), identified seasonal trends and spatial hotspots, and assessed inter-annual variability using Sentinel-5 Precursor (Sentinel-5P) satellite data integrated with GIS-based spatial analysis. Methods: Satellite-derived CO and aerosol data for Aba were obtained from Sentinel-5P (2019–2024). Datasets were accessed and processed within Google Earth Engine (GEE), where CO and aerosol bands were filtered by date and spatially constrained to the metropolitan boundary. Monthly and annual means were computed using custom JavaScript. Processed rasters were exported as GeoTIFF files and analysed in ArcGIS 10.7.1 to generate spatial distribution maps and classify concentration levels. Descriptive statistics and paired-sample t-tests were performed to evaluate inter-annual variability. Time-series analyses were used to assess seasonal trends and temporal fluctuations across the study period. Results: CO and aerosol levels exhibited pronounced seasonal peaks, consistently highest in February, and inter-annual fluctuations linked to post-pandemic recovery and energy use patterns. Central commercial and industrial areas consistently emerged as pollution hotspots, while peripheral zones recorded lower concentrations. Both pollutants responded to anthropogenic activity and policy changes, such as fuel subsidy removal, and their accumulation was modulated by seasonal climatic factors. Aerosols showed more persistent atmospheric presence than CO. This multi-year, high-resolution assessment provides a pollutant-specific baseline, filling gaps left by short-term ground-based studies and enabling evidence-based urban air quality management in mid-sized cities. Conclusion: This study quantified temporal and spatial dynamics of CO and aerosol concentrations in Aba (2019–2024) using Sentinel-5P and GIS analysis, revealing seasonal peaks, urban pollution hotspots, policy-sensitive variations, and providing a high-resolution baseline addressing gaps in continuous, pollutant-specific monitoring.