Abstract
Over the past two decades, the fast growth in travel has caused serious traffic congestion, which has made vehicular emissions to increase significantly. However, it is difficult to accurately estimate and quantify emissions using the current practice because of its reliance on transportation planning models, which are based on steady state hourly average and thus incapable of capturing the effects of traffic variations in the transportation system. This paper proposes an intermediate model that better estimates the link speed by considering a set of Emission Specific Characteristics (ESC) variables of the link. The improved link speed data will then be used to estimate emissions. The intermediate model is developed using multiple linear regression analysis. It is then calibrated, validated, and evaluated using a microscopic simulation method. 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.