Current frameworks for analyzing emissions performance of public transportation systems use top-down approaches that can often provide useful information at the network level but can be uninformative at the project level at which the influence of route and vehicle characteristics can significantly impact emission profiles of candidate transit options. This paper describes an alternative bottom-up framework that uses second-by-second travel activity data to estimate total power consumption and related emissions for propulsion purposes with application to electric rail transit systems. The model was developed and calibrated with data from Portland, Oregon, and was supplemented with activity data from Chicago, Illinois. The results showed a predicted 1% to 8% difference in expected power consumption relative to estimates derived from the national transit database. In addition, the results highlighted how the speed profile, configuration of the train in number of cars, and mix of power generation sources could significantly vary emissions performance across different service routes. The developed framework can serve as an important tool for a transit planner or policy maker to evaluate the emissions performance of electric rail transit options. This framework has the advantage of relevance at both the network and project levels. At the project level, users can easily perform detailed sensitivity analysis on aspects of transit services such as vehicle and fuel technologies, passenger loading profiles, train size, and track profile. This framework gives transportation planners a flexible and efficient tool for emissions performance analysis.