The MOtor Vehicle Emission Simulator (MOVES) model is published by the USEPA to estimate emissions from on-road vehicles in the United States. Traffic simulation model outputs and smart phone GPS data can provide detailed vehicle activity information in time and space. Coupling MOVES emission rates with various sources of high-resolution vehicle activity data can further advance 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 the 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 authors can be used to conduct the same emissions modeling in a fraction of the time, using a multidimensional array of MOVES outputs. The researchers configured MOVES to run on a distributed computing cluster, obtaining MOVES emission rate outputs for Atlanta for each vehicle class and model year at each operations, as a function of calendar year 2010-2020 (1-year interval) and 2025-2050 (5-year interval), local fuel (Summer fuel, Winter fuel, and Transition fuel), local I/M, meteorology (Temperature: 10-110 F with 5F-bin; Humidity: 0%-100% with 5%-bin ), and other variables of interest. For Atlanta, MOVES was run 22,491 times to generate the speed-bin and operating mode-bin emission rate matrices. The emission rate matrices allow users to employ big data inputs to and evaluate changes in emissions for dynamic transportation systems in near-real-time. In the case study, emission rate generation with MOVES-Matrix is 200-times faster than using the MOVES GUI in the same computer environment and predicts the same emissions results
