Urban populations in Latin America are highly exposed to traffic-related pollutants, yet monitoring networks remain limited. This study proposes a low-cost methodology to identify urban pollution hotspots in the city of Córdoba, Argentina, by categorizing 20 sites based on traffic categories using Google Traffic data. Measurements of PM_2.5, polycyclic aromatic hydrocarbons (PAHs), and equivalent sound pressure level (LA_eq) were conducted over a 21-day cold-season period. Mean PM_2.5 concentrations ranged from 7.5 to 27.3 µg/m³, and total PAHs ranged from 1.4 to 7.9 ng/m³. Sites with high and medium traffic density exhibited significantly higher PAH concentrations and noise levels, with LAeq₅ values exceeding 65 dB at all urban core locations. Conversely, PM_2.5 concentrations were higher at peripheral sites due to topography, dust resuspension, and wildfire events. Strong correlations were found between vehicular flow and noise (r = 0.94), and between heavy-vehicle proportion and noise (r = 0.60). The lifetime lung cancer risk associated with PAH exposure was classified as “low” according to USEPA criteria. This traffic-based categorization approach provides a rapid and cost-effective tool for identifying high-risk areas in resource-limited settings, supporting urban planning and public health interventions.