Data Sources for MOVES

Focus Area

Air Quality

Subcommittee

Air Quality

Status

Archived

Cost

$500,000-$750,000

Timeframe

1-2 years

Research Idea Scope

TERI Administrator Note – Selected as FY12 NCHRP Project 25-38

RESEARCH PROBLEM STATEMENT

 In the March 2, 2010 Federal Register (FR), EPA approved and announced the availability of the Motor Vehicle Emissions Simulator model (MOVES2010) for official use in all States, except for California.  The MOVES2010 model is the state-of-the-art upgrade to EPA’s modeling tools for estimating emissions from cars, trucks, motorcycles, and buses.  All State DOTs and MPOs will be required to use this model, after a two-year grace period, for new regional emissions analyses for transportation conformity determinations outside of California.  They will also be required to use this model in the near future for project-level transportation conformity hot-spot analyses after EPA approves the model for such analyses.  It is critical to ensure that the traffic and travel information going into this model maximizes its capability to accurately reflect the emissions for criteria pollutants and greenhouse gases associated with transportation programs and projects, including the emissions benefits associated with improved travel times, reductions in congestion levels, and stop and go traffic.  Research is therefore needed to identify, evaluate, and develop the most crucial traffic data sets for real time vehicle operating characteristics, including drive cycles, as inputs into the new MOVES model.   

LITERATURE SEARCH SUMMARY
 
While numerous research studies have been completed on traffic simulation and air quality models, there is a lack of information and knowledge on the appropriate travel and traffic input parameters to be used in the EPA MOVES2010 model to most accurately reflect various transportation programs, activities, and projects, including input parameters describing vehicle activity off the network.
 
Several recent research TRB papers start to address this issue.  For example, a Cornell University study entitled, “Diesel Particulate Matter Number Emissions: Evaluation of Existing Modal Emission Modeling Approaches”, examines existing modal emission modeling approaches in order to evaluate their ability of predicting diesel particle matter emissions emitted from a transit diesel bus.
 
The Beijing University has completed several recent TRB papers.   The first entitled, “Improved Vehicle Specific Power [VSP] Bins for Light-Duty Vehicles for Estimating Carbon Dioxide Emissions in Beijing” developed emission-specific VSP bins for estimating carbon dioxide (CO2) emissions for light-duty vehicles by using the real-world data collected in Beijing, China.  The VSP based information is a methodology in the EPA’s MOVES2010 model to generate emission rates.  The primary objective of a second paper entitled, “Analysis of Driving Behavior and Emission Characteristics for Diesel Transit Buses Using PEMS’ [Portable Emission Measurement System] Measurements”, was to collect real-world emission data from heavy-duty diesel buses using the PEMS, and driving activity data from diesel transit buses using the Global Positioning System (GPS) in Beijing.  The collected emission data were used to establish emission rates for VSP-bins, as well as to validate the VSP-based emission estimation approach for diesel transit buses.  In another paper entitled, “Distribution Characteristics of Vehicle Specific Power on Urban Restricted Access Roadways”, the study uses large samples of floating car data collected from the expressways in Beijing to associate the VSP distributions with various average travel speeds in order to examine how traffic conditions impact the VSP distributions.  This study indicates it is possible to develop VSP distributions mathematically for different road facilities and traffic conditions, which can be integrated with traffic simulation models for fuel and emission estimations.
 
Research in Progress includes:
 
Research by the University of Akron, Ohio, Integrating Traffic Operation with Emission Impact using Dual-loop Data, which has an objective to develop a framework to integrate improved dual-loop (in-pavement sensors) models with VSP-based models into a procedure for estimating emission impact of traffic flow operation over dual-loop monitoring stations in highways.
 
Research by the Texas A & M University, PEMS-based Approach to Developing and Evaluating Driving Cycles for Air Quality Assessment, the objectives of this research are to: 1) develop driving cycles for classified roads incorporating a vehicle’s driving activities and emission characteristics, using the data collected by PEMS, and 2) develop an evaluation approach of driving cycles in which the VSP is used to evaluate how well the driving cycles can represent the driving and emission characteristics on real roads.
 
Research by the Texas A & M University, An Evaluation of Mobile Source Greenhouse Gas Modeling Approaches for Traffic Management Assessment, the objectives of this research are to: 1) develop a mobile source GHG modeling approach based on VSP, and 2) develop evaluation approaches for traffic management strategies in terms of GHG emission control.
 
While these TRB papers and research activities start to evaluate the appropriate travel and traffic input parameters to be used in the EPA MOVES2010 model, there is an urgent need for quickly developing this information so that State DOTs and MPOs can accurately model the emissions benefits/impacts associated with transportation programs, activities, and projects. 

RESEARCH OBJECTIVE
 
The purpose of this research is to help provide transportation practitioners a better understanding of regional- and project-level traffic data for various transportation projects, and an increased capability of more accurately analyzing the air quality impact of such projects using MOVES2010. MOVES2010 requires a substantial amount of input data, some of which extends beyond the data requirements for previous emissions models.  For MOVES2010 regional (county)-level analyses, users must input the following data for the area of interest:

·         Road type distribution
·         Source (vehicle) type population
·         Monthly, daily, and hourly VMT fractions
·         Vehicle age distribution
·         Average speed distribution
·         Fuel formulation and supply
·         Meteorological data
·         Inspection and maintenance (I/M) coverage
 
For project-level analyses, users must input the following data for the individual links of interest:

·         Vehicle age distribution
·         Fuel formulation and supply
·         Meteorological data
·         I/M coverage
·         Operating mode[1] distribution, link drive schedule[2], or average speed
·         Off-network data
 
While state transportation agencies may be able to easily obtain some of the data listed above (e.g., meteorological data, I/M coverage), other types of data may be more difficult to collect.  The collection of accurate, recent traffic data may be especially problematic for state transportation agencies.   
 
The objectives of this proposal are to:
 
Evaluate the general availability of traffic data for MOVES, and identify areas where data may be lacking and/or difficult to obtain. 

1) Outline how the collected data fits into the state DOT environmental process and where the data is commonly located.  For example, identify which of the MOVES input parameters can and can not typically be found in engineering documents such as in a traffic engineering study, design report, or regional transportation plan. 

2) Identify the most crucial traffic data needs for MOVES.  Potential data needs include:

  • Project-level off-network data (i.e., hourly fraction of vehicles that start, hourly fraction of long-haul combination trucks in extended idle mode, hourly fraction of parked vehicles, and operating mode distribution).
  • Project-level operating mode distributions
  • Project-level drive schedules
  • Regional-level average speed distributions by road type
  • Regional-level monthly, daily, and hourly VMT fractions

3) Select several ideal study sites for collecting real-time traffic data and develop a data collection plan for each site
 
4) Collect data from each site and compare to any available existing data and/or traffic model outputs
 
5) Develop data sets that could potentially be used by MOVES users

6) Identify gaps in the existing methodologies and include research recommendations for filling these gaps.

[1] Operating modes are “modes” of vehicle activity that each have a distinct emission rate (e.g., operating mode “12” in MOVES represents “cruise/acceleration with a VSP between 0 and 2 and an instantaneous speed between 1 and 24 mph”). 

[2] A link drive schedule is entered in MOVES as precise speeds and grades per second of activity.

Urgency and Payoff

All State DOTs and MPOs, except for those in California, will have to use the EPA MOVES2010 model in the near future for all of their emissions modeling for transportation plans, programs and projects.  This will include analyses of the emissions associated with criteria pollutants under the Clean Air Act Amendments of 1990 for purposes of transportation conformity, and for NEPA purposes.  The MOVES 2010 model will also be used for modeling greenhouse gas (GHG) emissions.  Some State DOTs and MPOs have already started using the new model for GHG emissions analyses and it is highly likely that at some point in the near future, either because of new legislation or regulations, all States will be required to conduct GHG emissions analyses.  Since State DOTs and MPOs, except for those in California, will need to use this model for the foreseeable future it is important that the traffic and travel inputs to the model be as accurate as possible in order to provide for accurate emissions estimates. 

While many transportation systems and projects tend to reduce traffic congestion in urban areas, current analytical procedures tend to provide an average understanding of roadway operations such as average vehicle speeds, volume over capacity ratios, and are less precise than those applied to a specific roadway section.  This approach may not accurately reflect the emissions benefits of various types of transportation programs, activities, and projects.  For example, since up stream traffic flow influences the down stream flow (for instance, the roadway network covers many signalized intersections), the traffic operations analyses based on a segment of a network (or links) do not provide an accurate understanding of traffic flow on a specific link.  In addition, current procedures may not show the benefits of a system of ITS strategies if 24 hour averages are used rather than using hour by hour inputs.  Using hour by hour inputs will better reflect the emissions benefits of reducing congestion levels and the number of stops and starts during peak travel periods. The end result of using hourly data will be to show much more accurate emissions results.
EPA’s recent Draft Transportation Conformity Guidance for Quantitative Hot-spot Analyses in PM2.5 and PM10 Nonattainment and Maintenance Areas indicates that there are no default values available for any of the MOVES Off-Network inputs so users will need to input information describing vehicle activity in the off-network area being modeled.  This research will help provide State DOTs and MPOs with off-network data sets where possible, especially for the start fraction, extended idle fraction and parked vehicle fraction.

The anticipated benefits and results of this research include:

  1. Increased capability and accuracy of analyzing air quality emissions benefits/impacts on various transportation programs, activities, and projects.  Some of the transportation projects may not increase traffic flow speed but improve traffic flow quality by reducing congestion levels and stop and go traffic (i.e., coordinated signal systems etc.)
  2. More accurate understanding of air quality when analyzing complex transportation systems and projects.  Developing appropriate data sets will help to calibrate simulation models to the local conditions and provide a better understanding of area wide traffic flow.
  3. Development of the most critical traffic data sets that will be helpful for the State DOTs and MPOs who develop regional and project level emissions analyses for both criteria pollutants and GHG emissions.

Suggested By

ADC20, Transportation and Air Quality Committee, as specified in the TRB Research Needs Database, 2009; John Zamurs, Chair, AASHTO Standing Committee on the Environment/ Subcommittee on Air Quality, Climate Change and Energy

Submitted

02/18/2009