This study aimed to develop a robust methodology for collecting air quality data in Lagos, Nigeria to identify traffic-related predictors of air pollution. The researcher derived traffic density, road intersection density, and topography data from existing maps. These were standardized and combined to guide stratified random sampling of locations for collecting carbon monoxide, nitrogen dioxide, and particulate matter levels. Empirical Bayesian Kriging was used to interpolate the air quality data surfaces. Land use regression analysis showed a significant relationship between vehicular traffic and emissions. Further work will expand the study to additional LGAs based on health, population density, and vehicle registration criteria, and consider seasonal variations.