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NARSTO Workshop on Innovative Methods for Emission Inventory Development and Evaluation University of Texas, Austin October 14-17, 2003 |
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Automotive Particulate Matter and Gaseous Emission Factors from On-Road Measurement in Las Vegas, NV
Claudio Mazzoleni, Hampden D. Kuhns, Hans Moosmüller, Robert E. Keislar,
Peter W. Barber, Djordje Nicolic, Norman F. Robinson, and John G. Watson
Desert Research Institute, University of Nevada System, Reno, NV 89512
Detailed and accurate emission inventories are needed to design cost-effective measures to attain compliance with ambient air quality standards. The need for inventories of particulate matter (PM) emissions is driven by ambient PM standards and by the Regional Haze Rules. These regulations are designed to reduce health effects and visibility impairment due to elevated PM concentrations. Mobile sources make a significant, yet poorly quantified, contribution to total PM emissions. Remote sensing is an established and effective technology to determine gaseous emission factors for a large number (e.g., 105-106) of individual vehicles. Very recently, we have developed a remote sensor based on ultraviolet Lidar (light detection and ranging) and transmissometry for the measurement of automotive PM emission factors.
Here, we present the results of a large field study conducted in Las Vegas, NV. Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors were measured with a conventional gaseous remote sensor, while those for PM were measured with our new instrument. Fuel-based emission factors for nearly 150,000 vehicles were measured over a three-year period (spring and summer 2000-2002). Emission factor distributions are analyzed for each pollutant and averaged data are compared to values from previous studies and to the U.S. EPA´s models. The large skewness of these distributions is evident for both gaseous pollutants and PM. It has important implications for emissions reduction policy, since the majority of emissions are attributed to a small fraction of vehicles. Determination of vehicle speed, acceleration, and other vehicles characteristics, made it possible to stratify emissions by vehicle specific power, model year, fuel type, and weight class. The stratified results show important patterns in the distribution of emissions factors.