Abstract. Vehicular emissions contribute a significant portion to fine particulate matter (PM2.5) air pollution in urban areas. Knowledge of the relative contribution of gasoline- versus diesel-powered vehicles is highly relevant for policymaking, and yet there is a lack of an effective observation-based method to determine this quantity, especially for its robust tracking over a period of years. In this work, we present an approach to track separate contributions of gasoline and diesel vehicles through the positive matrix factorization (PMF) analysis of online monitoring data measurable by relatively inexpensive analytical instruments. They are PM2.5 organic and elemental carbon (OC and EC), C2–C9 volatile organic compounds (VOCs) (e.g., pentanes, benzene, xylenes, etc.), and nitrogen oxide concentrations. The method was applied to monitoring data spanning more than 6 years between 2011 and 2017 in a roadside environment in Hong Kong. We found that diesel vehicles accounted for ∼70 %–90 % of the vehicular PM2.5 (PMvehicle) over the years and the remainder from gasoline vehicles. The diesel PMvehicle during truck- and bus-dominated periods showed declining trends simultaneous with control efforts targeted at diesel commercial vehicles and franchised buses in the intervening period. The combined PMvehicle from diesel and gasoline vehicles by PMF agrees well with an independent estimate by the EC-tracer method, both confirming PMvehicle contributed significantly to the PM2.5 in this urban environment (∼4–8 µg m−3, representing 30 %–60 % in summer and 10 %–20 % in winter). Our work shows that the long-term monitoring of roadside VOCs and PM2.5 OC and EC is effective for tracking gaseous and PM pollutants from different vehicle categories. This work also demonstrates the value of an evidence-based approach in support of effective control policy formulation.