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<p>Air pollution poses significant environmental and public health challenges in rapidly urbanising regions of sub-Saharan Africa, where ground-based monitoring infrastructure remains limited. This study examined the spatiotemporal distribution of key air pollutants in Ado-Ekiti and its environs, Nigeria, from 2019 to 2024. Columnar concentrations of carbon monoxide (CO) and formaldehyde (HCHO) were retrieved from Sentinel-5P, while MODIS aerosol optical depth data was used to estimate particulate matter (PM<sub>2.5</sub> and PM<sub>10</sub>). Meteorological variables (rainfall, wind speed, and wind direction components u and v) were derived from the Weather Research and Forecasting model, and one week of ground-based measurements of pollutants were collected to enable correlation analysis with satellite-derived estimates. All datasets were aggregated to monthly and annual timescales, resampled to a 1&#xa0;km spatial resolution and re-projected to UTM Zone 31&#xa0;N. Results indicated that particulate matter dominated the pollutant profile, with annual mean concentrations of 59.37–65.29&#xa0;µg/m³ for PM<sub>2.5</sub> and 89.35–99.51&#xa0;µg/m³ for PM<sub>10</sub>, exceeding WHO guideline limits. Peak concentrations occurred during the Harmattan season, with PM₂.₅ &gt; 100&#xa0;µg/m³ and PM₁₀ &gt; 200&#xa0;µg/m³, driven primarily by Saharan dust transport and local activities. Mann-Kendall trend analysis revealed significant increasing trends in HCHO, PM<sub>2.5</sub>, and PM<sub>10</sub>, whereas CO showed no significant trend. Satellite-derived particulate estimates showed positive but weak correlations with ground-based particulate concentrations (<i>r</i> &lt; 0.20), whereas rainfall significantly reduced particulate levels, and meridional winds (v) facilitated long-range PM₁₀ transport. This study provides a significant integrated satellite model for air quality assessment in data-scarce urban environments while providing evidence to support targeted emission control strategies.</p>

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Assessing the spatiotemporal characteristics of urban air pollution in Ado-Ekiti and its environs, southwest Nigeria

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月31日

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  • Olawale Victor Oluwatuyi,
  • Francis Omowonuola Akinluyi,
  • Joseph Adeleke Adeyeye

摘要

Air pollution poses significant environmental and public health challenges in rapidly urbanising regions of sub-Saharan Africa, where ground-based monitoring infrastructure remains limited. This study examined the spatiotemporal distribution of key air pollutants in Ado-Ekiti and its environs, Nigeria, from 2019 to 2024. Columnar concentrations of carbon monoxide (CO) and formaldehyde (HCHO) were retrieved from Sentinel-5P, while MODIS aerosol optical depth data was used to estimate particulate matter (PM2.5 and PM10). Meteorological variables (rainfall, wind speed, and wind direction components u and v) were derived from the Weather Research and Forecasting model, and one week of ground-based measurements of pollutants were collected to enable correlation analysis with satellite-derived estimates. All datasets were aggregated to monthly and annual timescales, resampled to a 1 km spatial resolution and re-projected to UTM Zone 31 N. Results indicated that particulate matter dominated the pollutant profile, with annual mean concentrations of 59.37–65.29 µg/m³ for PM2.5 and 89.35–99.51 µg/m³ for PM10, exceeding WHO guideline limits. Peak concentrations occurred during the Harmattan season, with PM₂.₅ > 100 µg/m³ and PM₁₀ > 200 µg/m³, driven primarily by Saharan dust transport and local activities. Mann-Kendall trend analysis revealed significant increasing trends in HCHO, PM2.5, and PM10, whereas CO showed no significant trend. Satellite-derived particulate estimates showed positive but weak correlations with ground-based particulate concentrations (r < 0.20), whereas rainfall significantly reduced particulate levels, and meridional winds (v) facilitated long-range PM₁₀ transport. This study provides a significant integrated satellite model for air quality assessment in data-scarce urban environments while providing evidence to support targeted emission control strategies.