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.
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