Spatial and temporal variability of urban air quality across functional land-use zones in Eskişehir, Türkiye
DOI:
https://doi.org/10.32523/hym3fs97Keywords:
urban air quality, PM2.5, PM10, carbon dioxide, functional land use, spatial variability, kriging, GIS, sustainable urban planningAbstract
Urban air quality is spatially heterogeneous because emission intensity, land-use function, daily activity, seasonal energy demand, and atmospheric dispersion vary across the urban fabric. This study quantified the short-term spatial and temporal variability of PM2.5, PM10, and CO2 across ten functionally contrasting locations in Eskişehir, Türkiye. Field observations were conducted during four weeks in February and four weeks in May, with measurements collected on Mondays, Wednesdays, and Fridays during morning (08:30–10:30) and evening (17:00–19:00) periods. PM2.5 and PM10 were measured using a CEM DT-9880 portable particle counter, while CO2 was measured using an EXTECH EasyView 80 analyzer. Descriptive comparisons were combined with GIS-based Kriging interpolation to visualize broad concentration gradients. The results showed persistent spatial contrasts among industrial, residential, commercial, transportation, and vegetated environments. The Industrial Zone recorded the highest PM2.5 concentrations, reaching 543 μg/m³ in winter morning observations and 640 μg/m³ in winter evening observations. Winter CO2 reached 803 ppm at the Industrial Zone. Residential Area II also showed elevated particulate concentrations, whereas Urban Park and Urban Green Space generally exhibited lower values. Concentrations were generally higher in winter than in summer, and PM2.5 commonly increased from morning to evening. These patterns identify functional urban environments that warrant intensified monitoring and targeted management. The study does not establish source-specific causality because source apportionment and simultaneous site-level meteorological measurements were not available. Accordingly, the findings are interpreted as spatial and temporal contrasts within the monitored network rather than as regulatory compliance estimates or quantitative source contributions.
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