Framework for Context-Sensitive Spatially- and Temporally-Resolved Onroad Mobile Source Emission InventoriesEPA Grant Number: R834550
Title: Framework for Context-Sensitive Spatially- and Temporally-Resolved Onroad Mobile Source Emission Inventories
Investigators: Frey, H. Christopher , Rouphail, Nagui , Xuesong, Zhou
Institution: North Carolina State University , University of Utah
Current Institution: University of North Carolina , University of Utah
EPA Project Officer: Chung, Serena
Project Period: May 16, 2010 through May 15, 2013 (Extended to May 15, 2014)
Project Amount: $500,000
RFA: Novel Approaches to Improving Air Pollution Emissions Information (2009) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
NARSTO has identified onroad vehicles emissions as a high priority for improving emission inventories (EIs). This research will bridge the gap between transportation activity and multi-pollutant onroad vehicle emissions models. The objectives are to: (1) develop a robust, multi-scale methodology for estimating EIs at various spatial and temporal scales; (2) evaluate the utility of mesoscopic and microscopic transportation models to predict vehicle activity at sufficient resolution and in analyzing future vehicle, control or network design scenarios; and (3) quantify the relative contribution of vehicle type, vehicle activity and traffic control measures on the magnitude and variability in regional emission estimates.
The research includes the following tasks: (1) compile and catalogue “legacy” activity and emissions data; (2) select and construct the test-bed network; (3) develop a data collection plan to fill key gaps; (4) conduct field data collection from primary and secondary sources; (5) identify, review, and characterize a toolbox of traffic control measures (TCM’s); (6) develop and validate fuel use and emissions models; (7) quantify uncertainty; and (8) demonstrate methodology. Two themes are to: (1) appropriately link a mesoscopic or microscopic transportation model with an emissions estimation model; and (2) apply the integrated framework to quantify emissions at high spatial and temporal resolution in order to quantify baseline inventories suitable for air quality modeling and to support assessment of the effect of TCMs on a regional inventory. We will develop and demonstrate the methodology for a detailed case study for the Research Triangle Park (RTP) region of North Carolina.
The proposed approach will result in new methods for building, testing and improving emission inventories from mobile sources, taking into account the variety of data sources, modeling resources and traffic control measures that have been put in place in the last few years. We will quantify trade-offs between data / model resolution and the resulting estimates and variability in EIs, as well as the relative role of vehicle activity, vehicle class, and infrastructure design and operation in managing such inventories. We will produce a seamless interface between vehicle activity and fuel use and emission models across various temporal and spatial scales. We will demonstrate a detailed assessment of the effect of modifications to infrastructure, traffic control measures, and other approaches to influence vehicle operations as they pertain to energy use and emissions at local and regional scales. We will quantify uncertainty in the energy and emissions inventories for onroad vehicles. We will also address the impact of advanced vehicle technologies and alternative fuels on energy use and emissions.