Abstract-Many vehicle emission models are overly simple, such as the speed dependent models used widely, and other models are sufficiently complicated as to require excessive inputs and calculations, which can slow down computational time. We develop and implement an instantaneous statistical model of emissions (CO 2 , CO, HC, and NOx) and fuel consumption for light-duty vehicles, which is simplified from the physical loadbased approaches that are gaining in popularity. The model is calibrated for a set of vehicles driven on standard as well as aggressive driving cycles. The model is validated on another driving cycle in order to test its estimation capabilities. The preliminary results indicate that the model gives reasonable results compared to actual measurements as well as to results obtained with CMEM, a well-known load-based emission model. Furthermore, the results indicate that the model runs fast and is relatively simple to calibrate. The model presented can be integrated with a variety of traffic models to predict the spatial and temporal distribution of traffic emissions and assess the impact of ITS traffic management strategies on travel times, emissions, and fuel consumption.Index Terms-Instantaneous emissions modeling, integration of dynamic traffic and emission models, vehicle emissions and fuel consumption.

Methane (CH4) is an important greenhouse gas emitted by vehicles. We report results of a laboratory study of methane emissions using a standard driving cycle for 30 different cars and trucks (1995-1999 model years) from four different manufacturers. We recommend the use of an average emission factor for the U.S. on-road vehicle fleet of (g of CH/g of CO2) = (15 +/- 4) x 10(-5) and estimate that the global vehicle fleet emits 0.45 +/- 0.12 Tg of CH4 yr(-1) (0.34 +/- 0.09 Tg of C yr(-1)), which represents < 0.2% of anthropogenic CH4 emissions. This estimate includes the effects of vehicle aging, cold start, and hot running emissions. The contribution of CH4 emissions from vehicles to radiative forcing of climate change is 0.3-0.4% of that of CO2 emissions from vehicles. The environmental impact of CH4 emissions from vehicles is negligible and is likely to remain so for the foreseeable future.

The Kansas City Light-Duty Vehicle Emissions Study (KCVES) measured exhaust emissions of regulated and unregulated pollutants from 496 vehicles recruited in the Kansas City metropolitan area in 2004 and 2005. Vehicle emissions testing occurred during the summer and winter, with the vehicles operated at ambient temperatures. One key component of this study was the investigation of the influence of ambient temperature on particulate matter (PM) emissions from gasoline-powered vehicles. A subset of the recruited vehicles were tested in both the summer and winter to further elucidate the effects of temperature on vehicle tailpipe emissions. The study results indicated that PM emissions increased exponentially as temperature decreased. In general, PM emissions doubled for every 20 degrees F drop in ambient temperature, with these increases independent of vehicle model year. The effects of temperature on vehicle emissions was most pronounced during the initial start-up of the vehicle (cold start phase) when the vehicle was still cold, leading to inefficient combustion, inefficient catalyst operation, and the potential for the vehicle to be operating under fuel-rich conditions. The large data set available from this study also allowed for the development of a model to describe temperature effects on PM emission rates due to changing ambient conditions. This study has been used as the foundation to develop PM emissions rates, and to model the impact of ambient temperature on these rates, for gasoline-powered vehicles in the EPA's new regulatory motor vehicle emissions model, MOVES.

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