Air and Climate Change Research
Mobile Source Ozone Precursor Emissions Characterization and Modeling
The objective of this program is to characterize mobile source emissions which are one of the largest sources of tropospheric ozone precursor emissions (CO, NOx, and Volatile Organic Compounds (VOCs)) in the U.S. Due to the dynamic operation of motor vehicles, emissions are highly variable as a function of the mode of operation which is influenced by the driver, the type of vehicle, the roadway grade and the passenger or other load carried or pulled by the vehicle. As a consequence, the spatial distribution of emissions from one of the largest sources of ozone precursor emissions is poorly understood. Although average emissions over several square miles may be estimated by existing models, these models are not adequate for evaluating highway design and traffic effects. This program is researching and developing a new modal emissions model that can give detailed analyses of highway transportation control systems and is expected to provide important input on the effectiveness of future highway intelligent control systems.
Mobile Emissions Assessment
System for Urban and Regional Evaluation (MEASURE)
The Mobile Emissions Characterization Team's research objective is to develop and validate an air pollutant emissions estimation model for highway vehicles in order to gain a better understanding of the complex relationships between vehicle activity factors and emissions. In cooperation with our research partners at the Georgia Institute of Technology (GIT) and the North Carolina Department of Transportation (NCDOT), the model is being implemented for the Research Triangle Park area of North Carolina. The model, MEASURE, is built in a Geographic Information System (GIS) framework and goes beyond the capabilities of traditional mobile emissions models by estimating emissions for specific vehicle and engine operating modes (engine starts, acceleration, deceleration, idling etc.). The premise is that this approach can produce more accurate estimates of actual on-road emissions, provide better spatial and temporal resolution of the emissions, and be sensitive to how changes in highway design and functional characteristics affect emissions rates. The model can be used to produce more accurate emissions data for input to air quality dispersion models and the evaluation of the effectiveness of alternative mobile source emissions control scenarios. To support model development and validation, the team develops data acquisition strategies and conducts field studies to collect real-world vehicle activity and emissions data. The team employs remote sensing devices, automobiles and trucks equipped with on-board instrumentation, and other techniques to collect these data.
Remote sensing of automobile emissions is a technique developed in the late 1980s. The remote sensing device (RSD) uses infrared (IR) and, in some cases, ultraviolet (UV) spectroscopy to measure the concentrations of pollutants (e.g., CO2, CO, HCs, and NO) in exhaust emissions as the vehicle passes a sensor on the roadway. The RSD consists of IR and UV instruments that measure the exhaust emissions as the vehicle passes through the IR/UV beams and a monitoring station inside a van. RSDs have been used to develop a profile of the emission characteristics of the overall fleet of motor vehicles in metropolitan areas and/or to identify those vehicles known as "super emitters," which are responsible for much of automotive emissions. In addition to the source and detector, remote sensors may be equipped with meteorological stations and speed/acceleration systems which are important in interpreting exhaust measurements by the RSD.
Additional Resources Outside the U.S. EPA Domain
Georgia Institute of Technology: