Spatial variability and meteorological associations of pm₂.₅ and pm₁₀ across paved and unpaved roads in Abeokuta, Nigeria

Urban Particulate Matter (PM) in rapidly expanding tropical cities is strongly associated with boundary-layer processes, surface characteristics, and mechanical resuspension mechanisms. Understanding the spatial behavior of fine (PM₂.₅) and coarse (PM₁₀) aerosols across contrasting surface types is critical for characterizing urban atmospheric dynamics. This study investigates the spatial variability, coarse-particle contribution, and meteorological associations governing PM₂.₅ and PM₁₀ concentrations across paved and unpaved urban corridors in Abeokuta, southwestern Nigeria. Fourteen sampling locations (S1–S14) were monitored for PM and key meteorological parameters (temperature, relative humidity, and wind speed). Statistical analysis, Air Quality Index (AQI) classification, correlation modeling, and geospatial interpolation were employed to evaluate distribution patterns and atmospheric controls. The PM₂.₅/PM₁₀ ratio was additionally used as a diagnostic indicator of dominant particle-mode contributions. Both PM₂.₅ and PM₁₀ exhibited significant spatial heterogeneity ( p < 0.05), with unpaved corridors showing enhanced coarse-mode dominance and elevated particulate loading. Interpolated concentration fields revealed distinct interpolated high-concentration zone clusters aligned with high-traffic and mechanically disturbed zones. Lower PM₂.₅/PM₁₀ ratios indicated greater relative coarse-particle contributions at several sites, while higher ratios indicated increased fine-particle fractions; however, specific emission sources could not be confirmed. Wind speed and relative humidity showed measurable influence on dispersion and suspension dynamics, while temperature remained relatively uniform during the observation period. The results highlight strong surface-type control on particulate emission and redistribution, emphasizing the role of mechanical turbulence and boundary-layer interactions in shaping urban aerosol fields. The integration of ratio diagnostics with spatial interpolation provides enhanced process-based interpretation of urban aerosol behavior in tropical environments.