Correlation assessment of air quality parameters and climate variables in Benin City, Southern Nigeria: a remote sensing approach

Abstract

Air pollution is a pressing environmental and health challenge, particularly in rapidly growing urban regions. Effective mitigation requires understanding how meteorological conditions shape pollutant behavior. Traditional ground-based monitoring offers valuable insights but often lacks spatial coverage, limiting assessment of regional-scale interactions. To address this gap, this study applies satellite remote sensing and reanalysis datasets to evaluate relationships between atmospheric pollutants and climate variables. The Shapiro-Wilk test was applied to verify normality prior to correlation analysis. Pearson (r) and Spearman (ρ) coefficients were then used to examine associations between pollutants and meteorological conditions. Results revealed clear seasonal patterns, with elevated pollutant levels during the dry season and lower concentrations during the wet season. Carbon monoxide exhibited a strong positive correlation with temperature (r = 0.749, ρ = 0.704), a moderate negative correlation with rainfall (r = -0.768, ρ = -0.812), and a weak negative correlation with wind speed (r = -0.271, ρ = -0.288). Sulfur dioxide showed weak association with temperature (r = -0.036, ρ = -0.082) and moderate negative correlation with rainfall (r = -0.392, ρ = -0.425). Aerosols correlated positively with temperature (r = 0.621, ρ = 0.616), negatively with rainfall (r = -0.713, ρ = -0.787), and weakly with wind speed (r = -0.285, ρ = -0.298). These findings emphasize the critical role of climate in shaping air quality.