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<p>This study analyzed the level and temporal variations of the air pollutants with the prevailing meteorological variables using four months dataset (April 4-July, 2022) in Osogbo, Nigeria. Multiple Linear Regression was employed to assess the relationships while Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) was adopted to identify pollutants transport path. The results revealed that PM<sub>2.5</sub> levels exceeded the national and international standards of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:40\:\)</EquationSource> </InlineEquation>and <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\:35\:{\upmu\:}\text{g}{\text{m}}^{-3}\)</EquationSource> </InlineEquation>, respectively due to strong anthropogenic influences, while Ozone, CO and CH<sub>4</sub> showed two distinct diurnal peaks linked to traffic emissions. Also, air pollutants had weak correlations ranging from − 0.34 to 0.39 with meteorological variables and evidence from trajectory analysis highlighted both local and transboundary pollution sources, underscoring the need for seasonally tailored mitigation strategies.</p>

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Temporal variations of air pollutants and meteorological variables over a tropical station in Osogbo, Nigeria

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月6日

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  • Opeyemi R. Omokungbe,
  • Ayodele P. Olufemi,
  • Oluwaseun O. Ajileye,
  • Babatunde A. Rabiu,
  • Olubusayo F. Oladejo,
  • Adebiyi S. Adebayo,
  • Oghenenyovwe Ovie,
  • Gregory S. Jenkins

摘要

This study analyzed the level and temporal variations of the air pollutants with the prevailing meteorological variables using four months dataset (April 4-July, 2022) in Osogbo, Nigeria. Multiple Linear Regression was employed to assess the relationships while Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) was adopted to identify pollutants transport path. The results revealed that PM2.5 levels exceeded the national and international standards of \(\:40\:\) and \(\:35\:{\upmu\:}\text{g}{\text{m}}^{-3}\) , respectively due to strong anthropogenic influences, while Ozone, CO and CH4 showed two distinct diurnal peaks linked to traffic emissions. Also, air pollutants had weak correlations ranging from − 0.34 to 0.39 with meteorological variables and evidence from trajectory analysis highlighted both local and transboundary pollution sources, underscoring the need for seasonally tailored mitigation strategies.