Sensitivity of emissions predictions based on GPS-based cycle data and assumptions of idle cutpoints

Idle emissions account for a significant portion of total emissions of bus operations. Accurate monitoring and quantification of idle emissions is an important first step towards designing effective idle reduction policies that target criteria pollutants and greenhouse gas (GHG) emissions. The wide availability of global positioning system (GPS) tracking devices has enabled real-time, high resolution monitoring of idle activities. However, GPS-based data also present a unique challenge in idle emissions modeling because idle activities may not be easy to define due to GPS wander. A spreadsheet toolset for conducting emissions sensitivity analyses for idle cutpoints is presented, with the goal of providing a practical solution to using GPS vehicle tracking data properly in emissions modeling. The results show that the cut-off speed for idling tends to significantly differ across devices, emphasizing the need for users to carefully select the idle cutpoint. The implications on emissions predictions are exemplified in a case study using GPS data collected on two bus routes in Atlanta, GA. Recommendations are given for the treatment of GPS data in idle classification and emissions modeling. This is an abstract of a paper presented at the 106th AWMA Annual Conference and Exhibition (Chicago, IL 6/25-28/2013).