The Motor Vehicle Emission Simulator (MOVES) model was developed by the US Environmental Protection Agency (USEPA) to estimate emissions from on-road and off-road vehicles in the United States. The MOVES model represents a significant improvement over the older MOBILE series of modes, primarily because emission rates are now much more modal in nature, representing emissions as a function of power surrogates, which depend on speed and acceleration. Traffic simulation model outputs and smartphone GPS data can provide second by-second vehicle activity data in time and space, including vehicle speed and acceleration data. Coupling high-resolution vehicle activity data with appropriate MOVES emission rates further advances research efforts designed to assess the environmental impacts of transportation design and operation strategies. However, the MOVES interface is complicated and the structure of input variables and algorithms involved in running MOVES to assess operational improvements makes analyses cumbersome and time consuming. The MOVES interface also makes it difficult to assess complicated transportation networks and to undertake analyses of large scale systems that are dynamic in nature. The MOVES-Matrix system developed by the research team can be used to perform emissions modeling activities in a fraction of the time compared to running MOVES. The approach involves running the MOVES model iteratively, across all potential input variable combination, and using the resulting multidimensional array of pre-run MOVES outputs in emissions modeling.

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Eco-driving has significant potential to reduce fuel consumption and emissions from transit operations. Analyses were conducted of 68 thousand miles of real-world operations data from 26 buses, collected from local transit service provided by the Metropolitan Atlanta Rapid Transit Authority (MARTA), and express bus service provided by the Georgia Regional Transportation Authority (GRTA). The analysis utilized second-by-second operations data collected via global positioning system (GPS) devices from buses operated by these transit agencies. The researchers simulated the implementation of transit eco-driving strategies, based on the modal emissions modeling framework employed by the Motor Vehicle Emission Simulator (MOVES) designed to reduce engine load and emissions. This algorithm seeks to minimize fuel consumption by limiting instantaneous vehicle specific power (VSP), while maintaining average speed and conserving total distance. Fuel consumption and fuel-cycle emissions were compared across the monitored driving cycles and their modified eco-driving cycles.The savings from eco-driving were also compared against expected fuel and emissions reductions via conversion of the transit fleets to compressed natural gas (CNG), which is another popular fuel conservation strategy. The transit eco-driving strategy showed a 5% reduction in fuel consumption and fuel cycle greenhouse gas (GHG) emissions for MARTA’s 508-bus fleet (~35% diesel/65% CNG), and a 7% reduction in fuel consumption for GRTA’s 166-bus diesel fleet. The fuel savings translate to about 300,000 gallons of diesel fuel equivalent per year for MARTA and 55,000 gallons of diesel per year for GRTA. Eco-driving was also shown to reduce fuel use and emissions for CNG fleets. Eco-driving training can readily be implemented if speed/acceleration activity is monitored. Because eco-driving does not require significant capital investment it is a potentially very cost-effective strategy for local and express bus transit operations.

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The Fuel and Emissions Calculator (FEC) is an operating-mode-based, life-cycle emissions modeling tool developed by the Georgia Institute of Technology researchers. The primary purpose of the FEC is to assist fleet owners and managers, regulatory agencies, and policy analysts in assessing the energy and emissions impacts of fleet alternatives. The FEC’s modeling approach estimates emissions as a function of engine load, which in turn is a function of vehicle service parameters, allowing modelers to account for local on-road operating mode conditions as model inputs. The functional modules are embedded in an Excel spreadsheet platform for all current model versions. The open platform allows users to see all input data and every calculation, which makes the model transparent and accessible for most users. With Version 2.0 of the model, an online Python version of the model has also been developed. The Python version enhances model performance, and provides functionality for advanced users who may wish to link the FEC with other modeling tools, such as travel demand or simulation models. The first Fuel and Emissions Calculator (Version 1.0), known as ‘FEC for transit fleets,’ was originally developed by Georgia Tech researchers in 2013-2014 for transit bus, shuttle bus and rail systems (ORNL and Georgia Tech, 2014). This report first summarizes the FEC Version 2.0 model’s main features. The generic methodology that is applied to all transportation modes is introduced in Chapter 2, which includes modules for scenario setting, energy consumption, onroad emission rates, life-cycle assessment, and cost-effectiveness. The model specifications for individual transportation modes are introduced in Chapter 3, and case study examples are provided to help users prepare customized analysis for their own fleets. The key considerations for establishing the online FEC are discussed in Chapter 4. Current research achievements and ongoing work to update and improve the FEC are provided in the final Chapter.

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