Estimation of Vehicular Emissions by Capturing Traffic Variations

Over the past decades, the fast growth in travel has increased traffic congestion, which in turn has increased vehicular emissions significantly. It is difficult to accurately estimate and quantify emissions with current practice because of its reliance on transportation planning models that are based on steady state hourly averages and thus are incapable of capturing the effects of traffic variations in the transportation system. This paper proposes an intermediate model component that can better estimate link speed by considering a set of Emission Specific Characteristics (ESC) for each link. The improved link speed data will then be used to estimate emissions. The intermediate model component is developed using multiple linear regression; it is then calibrated, validated, and evaluated using a microscopic simulation model. The evaluation results show that the proposed emission estimation method performs better than the current practice and is capable of estimating time-dependent emissions if traffic sensor data are available as model input.