Intra-urban variability of long-term exposure to PM_2.5 and NO₂ in five cities in Colombia

Rapidly urbanizing cities in Latin America experience high levels of air pollution which are known risk factors for population health. However, the estimates of long-term exposure to air pollution are scarce in the region. We developed intraurban land use regression (LUR) models to map long-term exposure to fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) in the five largest cities in Colombia. We conducted air pollution measurement campaigns using gravimetric PM_2.5 and passive NO₂ sensors for 2 weeks during both the dry and rainy seasons in 2021 in the cities of Barranquilla, Bucaramanga, Bogotá, Cali, and Medellín, and combined these data with geospatial and meteorological variables. Annual models were developed using multivariable spatial regression models. The city annual PM_2.5 mean concentrations measured ranged between 12.32 and 15.99 µg/m³ while NO₂ concentrations ranged between 24.92 and 49.15 µg/m³. The PM_2.5 annual models explained 82% of the variance (R²) in Medellín, 77% in Bucaramanga, 73% in Barranquilla, 70% in Cali, and 44% in Bogotá. The NO₂ models explained 65% of the variance in Bucaramanga, 57% in Medellín, 44% in Cali, 40% in Bogotá, and 30% in Barranquilla. Most of the predictor variables included in the models were a combination of specific land use characteristics and roadway variables. Cross-validation suggests that PM_2.5 outperformed NO₂ models. The developed models can be used as exposure estimate in epidemiological studies, as input in hybrid models to improve personal exposure assessment, and for policy evaluation.