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The contribution of lubricating oil to particulate matter (PM) emissions representative of the in-use 2004 light-duty gasoline vehicles fleet is estimated from the Kansas City Light-Duty Vehicle Emissions Study (KCVES). PM emissions are apportioned to lubricating oil and gasoline using aerosol-phase chemical markers measured in PM samples obtained from 99 vehicles tested on the California Unified Driving Cycle. The oil contribution to fleet-weighted PM emission rates is estimated to be 25% of PM emission rates. Oil contributes primarily to the organic fraction of PM, with no detectable contribution to elemental carbon emissions. Vehicles are analyzed according to pre-1991 and 1991-2004 groups due to differences in properties of the fitting species between newer and older vehicles, and to account for the sampling design of the study. Pre-1991 vehicles contribute 13.5% of the KC vehicle population, 70% of oil-derived PM for the entire fleet, and 33% of the fuel-derived PM. The uncertainty of the contributions is calculated from a survey analysis resampling method, with 95% confidence intervals for the oil-derived PM fraction ranging from 13% to 37%. The PM is not completely apportioned to the gasoline and oil due to several contributing factors, including varied chemical composition of PM among vehicles, metal emissions, and PM measurement artifacts. Additional uncertainties include potential sorption of polycyclic aromatic hydrocarbons into the oil, contributions of semivolatile organic compounds from the oil to the PM measurements, and representing the in-use fleet with a limited number of vehicles.

The growing number of health studies identifying adverse health effects for populations spending significant amounts of time near large roadways has increased the interest in monitoring air quality in this microenvironment. Designing near-road air monitoring networks or interpreting previously collected near-road monitoring data is essential for transportation system planning, environmental impact assessments, and exposure assessments in health studies. For these applications, care must be taken in determining the pollutants of interest for both air quality and health assessments. In addition, planners and data analysts need to evaluate and understand the potential influence of the roadway type, design, and presence of roadside structures on the potential transport and dispersion of traffic-emitted pollutants on these air quality and health evaluations. This paper summarizes key factors related to the collection and interpretation of near-road air quality data from the perspective of the pollutants of interest and the location of the monitoring sites.

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