Development of Local Emissions Rate Model for Light-Duty Gasoline Vehicles: Beijing Field Data and Patterns of Emissions Rates in EPA Simulator

Abstract

A local emissions rate (ER) model is an important tool that is often combined with vehicle activity data in assessing the effect of traffic control strategies on emissions. Such a model is especially critical in developing countries where local emissions data are either unavailable or limited. This study sought to develop a local ER model for light-duty gasoline vehicles (LDGVs) based on limited emissions testing data from Beijing, emissions factors in the China vehicle emission model, and the regular patterns of ERs in the Motor Vehicle Emission Simulator (MOVES) program. To this end, the research team first analyzed the characteristics of vehicle emissions on the basis of field data collected in Beijing. Then the authors summarized the regular pattern of ERs for LDGVs embedded in the MOVES model and examined consistency of normalized ERs derived from Beijing and the MOVES program. The normalized mean square error was used to evaluate the level of consistency. When consistency was sufficiently high, the regular pattern of ERs in the MOVES program was used to fill the missing field emissions data. Development of the model involved four essential elements: (a) data-driven ERs, (b) a supplement for high-power operating modes, (c) modeling ERs of zero-mile-level emissions, and (d) development of a deterioration model of ERs. On the basis of the proposed model, a local database of ERs for LDGVs was established and applied to assess the emissions benefit of electronic toll collection lanes.