2012 Progress Report: 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
Current Investigators: Frey, H. Christopher , Rouphail, Nagui , Xuesong, Zhou
Institution: North Carolina State University
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 Period Covered by this Report: May 16, 2012 through May 15,2013
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
To: (1) develop a robust, multi-scale methodology for estimating EIs at various spatial and temporal scales; (2) evaluate the utility of meso-scopic 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.
For Task 1, we have reviewed prior in-use emissions data collected from 2008 to 2013 to create a ‘legacy’ archive of vehicle fuel use and emissions rates based on in-use measurements on selected routes using a Portable Emissions Measurement System (PEMS). We have identified a total of 100 light duty vehicles, including 67 passenger cars and 33 passenger trucks, for which we have conducted PEMS measurements as part of this and other projects. We have analyzed these data for up to 6 real-world driving cycles per vehicle, for approximately 600 vehicle-cycle pairs, and are using these data for a comparison to emission factors estimated from the MOVES model.
During the reporting period, the focus in Tasks 2 and 4 was on enhancing and verifying meso-scopic and microscopic transportation models to predict vehicle activity at sufficient resolution. For Task 3, we have continued to collect field data to augment the legacy database. For Task 4, we conducted field data collection between August 2012 and March 2013 on 25 light duty gasoline vehicles. In-use measurements of CO2, CO, hydrocarbons, and NO were made using a Portable Emissions Measurement System (PEMS). Vehicle activity was measured using an On-Board Diagnostic (OBD) data logger for the vehicle Electronic Control Unit (ECU) and a Global Positioning System (GPS) receiver for vehicle location and elevation.
As part of Task 5, we have completed the identification, characterization and selection of the traffic control measures to be applied to the meso/micro simulation models, in order to test their effectiveness on reducing the emission inventory on the road network.
For Task 6, we have continued development of a simplified vehicle emissions model that we refer to as “MOVES Lite.” We have developed MOVES Lite to include five key vehicle types and to span vehicle ages from 0 to 30 years old. MOVES Lite currently is configured to estimate cycle average emission rates for any user-specified driving cycle for CO2, CO, Hydrocarbons (HC), and NOx. MOVES Lite has been evaluated by comparing its predictions to those of the MOVES model for the same cycles.
For Task 7, we have conducted preliminary sensitivity analyses. Task 8 is mainly focused on demonstration of an integrated method for quantification of vehicle emissions as part of traffic simulation modeling. As an initial part of Task 8, a case study was performed to test the proposed multi-scenario, multi-resolution modeling/simulation methodology using a small subarea of the Salt Lake regional network. Several scenarios were constructed to test the effects of different work zone schedules and variable message signs in different scenarios.
We have completed compilation of legacy data and field measurements of real-world vehicle activity, fuel use, and emissions (Tasks 1, 3, and 4). We have completed identification and construction of the test network (Task 2) and identification and review of traffic control measures (Task 5). We have completed most of the work needed on development and validation of fuel use and emission models (Task 6), with some work remaining to finalize the simplified MOVES model and to compare predicted emission factors from MOVES to empirical data measured in the field. MOVES lite is incorporated into DTAlite. After completing testing of DTAlite, The combined traffic simulation and emissions model will be applied to further sensitivity and uncertainty analysis (Task 7) and illustrative case studies (Task 8) to demonstrate how the onroad tailpipe emissions inventory is sensitive to traffic control and management measures.