Abstract Motor vehicles are a significant source of airborne polycyclic aromatic hydrocarbons (PAH) in many urban areas. Traditional approaches used in determining the relative contributions of individual vehicle types to the total amount of PAH in air have been based on the analysis of integrated samples of airborne particles and gases for the presence of chemical tracers indicative of the vehicles from which the chemicals derived. As an alternative, we have used a photoelectric aerosol sensor (PAS) capable of measuring PAH levels in real-time in the emissions plumes from motor vehicles. We placed the PAS near a traffic-light in Kenmore Square, a busy crossroads in downtown Boston (MA, USA). A video camera co-located at the site recorded the vehicles passing the sensor, and this record was correlated with the PAS data. During a 5-day monitoring period (∼59 h) in the summer of 1998, over 34 000 motor vehicles were counted and classified and over 24 000 PAS readings were recorded (frequency=1/8.6 s). The composition of the vehicle population was 94% passenger vehicles, 1.4% buses, 2.6% small trucks, 1.3% medium trucks, 0.35% large trucks, and 0.45% garbage and construction trucks. In analyzing the PAS data, it was assumed that the highest PAS measurements — those that exceeded the 95% critical level of the 5-min moving average of all the PAS measurements — were indicative of primary vehicular emissions. We found that ∼46% of the mass of particle-bound PAH (i.e. ∼46% of the integrated area under the PAS signal vs. time plots) was attributable to primary emissions from motor vehicles passing the sensor. Of this, 35–61% was attributable to passenger vehicles (cars, pickup trucks, and sports utility vehicles) and 39–65% was attributable to non-passenger vehicles [buses (14–23%), small trucks (12–20%), medium trucks (8.4–14%), large trucks (2.9–4.8%) and garbage and construction trucks (1.9–3.2%)]. Our results suggest that on a per vehicle basis, buses and trucks — the majority of which run on diesel fuel — emitted greater amounts of particle-bound PAH than passenger vehicles. Overall, we found that real-time photoelectric aerosol sensing (in combination with video photography) is useful for estimating the contributions of airborne PAH from different vehicle types. Due to the physical constraints of our monitoring site and the high volumes of traffic, however, it was not possible to uniquely attribute PAS signals to individual vehicles.