Improving Emission Estimates Using Driving Cycles for Higher Road Grades

Focus Area

Air Quality


Air Quality






1-2 years

Research Idea Scope

EPA suggested in response to a comment in the last MOVES Model Review Workgroup that grade-specific drive cycle data (second-by-second speeds) be used instead of model default data (which generally correspond to travel at zero grade) as a means to improve emission estimates for vehicles on roads with higher grades. Vehicles travelling on roads with higher road grades have increased power demands (which tends to increase emission rates) and typically operate at lower speeds (particularly heavy trucks). Based on MOVES3 and previous versions of that model, emission rates can be significantly under-estimated at higher speeds and over-estimated at moderate speeds depending on the pollutant, vehicle type and roadway class. To assess this problem, driving cycles for higher road grades are needed for all vehicle types but particularly heavy-duty diesel trucks that emit fine particulate matter (PM2.5) at high rates, which can pose relatively high health impacts especially for those with respiratory conditions and may be of increased concern for areas with environmental justice (EJ) communities. Driving cycles for higher road grades are also important for estimating greenhouse gas (GHG) emissions per CEQ guidance for freeways that generally operate at relatively higher speeds than other roadway classes. Note state DOTs have the traffic expertise and therefore are in a much better position to assess driving cycles than EPA.

To validate the use of driving cycles for higher road grades as a means to improve emission modeling for NEPA analyses conducted by state DOTs, this study would first review the literature to identify available sources of the drive cycle data for higher road grades, e.g., via the Texas Transportation Institute and/or the National Center for Sustainable Transportation (NCST) at Georgia Tech. Ideally, drive cycle data would be obtained for light- versus heavy-duty vehicles (LDVs and HDVs respectively) in addition to the on-road fleet average. The sensitivity of the new MOVES4 model to the use of drive cycle data for high road grades versus default data would then be tested by comparing modeled emission factors for the specific speeds, road grades and road and vehicle types for which the high road grade drive cycle data are available. The comparisons would be done for pollutants typically modeled in NEPA studies at the project-scale, including not only PM2.5 and GHGs but also carbon monoxide (CO). To the extent that drive cycle data are available, emission factor comparisons would be conducted for LDVs, HDVs and the on-road fleet average. For a broader perspective, plots of emission factors by speed covering the full range of positive road grades typically encountered in practice would be compared for reasonableness for modeling based on the high-road grade drive cycle data versus the default data. The comparisons would be done by vehicle and road type.

Optionally, a field study could also be done to collect drive cycle data covering a broad range of road grades and speeds that would allow for a more comprehensive review. Portable emission monitoring systems (PEMS) could be used in the field study to collect emission data in addition to the drive cycle data for LDVs and HDVs. The budget and timeframe for this optional field study would be additional to those suggested above.

Urgency and Payoff

The potentially substantial uncertainty in emission estimates for high road grades may become an increasing cause for concern for NEPA air quality studies, particularly if it leads to significant underestimates of emissions and local air pollutant concentrations for roads in or near EJ communities. This study would determine whether those potential concerns can be effectively addressed through the use of representative drive cycle data for higher road-grades instead of default drive cycle data. It may also help provide more representative mitigation options for communities.

Suggested By

Christopher Voigt

[email protected]