Metropolitan areas in nonattainment for transportation-related air pollutants rely on transportation control measures (TCMs) to reduce emissions and meet clean-air goals. However, since traditional transportationrelated air quality models use emission rates based on average speeds, only TCMs that either increase or decrease vehicle activity to speeds in which emissions are lower show reductions in output of air pollutants. In recent years, transportation air quality analysis has shifted to an activityspecific modeling approach that correlates emissions to vehicle operating mode. With an activity-specific approach, the emission reduction potential of a TCM can be evaluated by its ability to decrease time spent in modes in which emissions are disproportionately elevated. Signal timing improvements are attractive TCMs for traffic flow improvement. However, with traditional modeling, they may greatly decrease extremes in modal activity yet not show significant emission reduction if only moderate changes in average speed are realized. The benefits of using activityspecific modeling for evaluation of improved signal coordination as a TCM are described. A brief overview of the development of an activityspecific carbon monoxide emission rate model is provided, data collection for on-road vehicle activity estimates is briefly outlined, and a comparison of traditional emission modeling versus activity-specific modeling is provided to estimate the air quality benefits from improved coordination at a study intersection. Results for the study intersection indicate that more significant reductions in carbon monoxide emissions are realized using an activity-specific approach than with traditional methods.
