Forecasting Travel Activity Input Data for Project-Level Air Quality Analyses

Focus Area

Air Quality


Air Quality






1-2 years

Research Idea Scope

Effective December 20, 2012, a new era in air
quality analyses for transportation projects began as federal transportation
conformity rule requirements and associated guidance issued by the US EPA for
the application of more complex emission (MOVES) and air quality dispersion
(CAL3QHCR and AERMOD) models became effective. Where applicable, these new
conformity requirements are expected to significantly increase the time and
resource requirements for project-level air quality analyses. Furthermore,
there may be ramifications with respect to the more widely applicable
requirements under the National Environment Policy Act (NEPA). They also create
some uncertainty regarding expectations for the underlying traffic forecasts,
as corresponding best practices for generating traffic forecasts. These new
procedures will require improved characterization of the vehicle fleet,
particularly for diesel trucks and buses as identified in the regulation, and
provide expanded capabilities to represent the variability of activity of
traffic both on the road and at off-road terminals. Further guidance to support
the more complex emission and air quality modeling requirements have not yet
been initiated. It is proposed for development in this study.

The proposed development of best practices or
a practical guide for travel data and forecasts would also be consistent with
new federal requirements specified in the Moving Ahead for Progress in the 21st
Century Act (MAP-21)(Public Law 112-141), which was signed on July 6, 2012, and
the US DOT Every Day Counts initiative. Sections of MAP-21 of particular
relevance include:

•             Section
1301(b)(2)(A), which makes a general call “…to develop and advance the use of
best practices to accelerate project delivery and reduce costs across all modes
of transportation and expedite the deployment of technology and innovation”,

•             Section
1503(j)(1), which calls for “advanced modeling technology” that among other
objectives can  (-(A)) “…accelerate and
improve the environmental review process…”, and

•             Section
1503(j)(2), which calls for “…the use of advanced modeling technologies
during environmental … processes…”.


In areas that do not meet the National
Ambient Air Quality Standards NAAQS) for Particulate Matter (PM2.5 or PM10) or
Carbon Monoxide (CO), projects must demonstrate that they meet the air quality
conformity requirements before funding may be approved. The new regulations
(effective December 2012), created some uncertainty in adopting the new
procedures. The requirements are affecting over 50 metropolitan locations with
a combined population of over 106 million people in nonattainment areas for the
PM2.5 standards (daily and/or annual) alone.


For background, the new EPA procedures
involve the adoption of a new emissions model (MOVES) in transportation air
quality studies along with dispersion models (CAL3QHCR and AERMOD) which have
not been widely used in the transportation sector. The National Research
Council had presented a critique of the previous emissions model (MOBILE) with
one of the deficiencies related to its inability to properly reflect emissions
at the project-level scale. Emissions are known to vary with operations (e.g.,
braking, acceleration) and operations in MOBILE were fixed by defined drive
cycles. The design of the new MOVES 
model was intended to address the deficiencies identified in the NRC
critique, including for example the capability to differentiate these modal
operations. However, to do so, input data must be provided at a level of detail
appropriate to the level of analysis needed to meet regulatory requirements.
The question then arises: what level of analysis is appropriate to meet the
various regulatory requirements for all pollutants, for both conformity and


For example, for a relatively small or
non-controversial project, particularly one in which NEPA applies but
conformity does not,  practitioners may
reasonably apply the most straightforward approaches available for traffic
modeling to generate basic forecasts for traffic volumes and speeds, including
procedures derived from the Highway Capacity Manual. This approach would
typically involve the lowest cost and require the least time. It would also be
consistent with historical practice for modeling carbon monoxide, e.g., for
projects involving a categorical exclusion (CE) or an environmental assessment


For a project with more potential air quality
impact or one involving greater controversy, a more refined approach that
better utilizes the capabilities of the new MOVES model may be preferred, one
for example that does not rely upon the use of average speeds and associated
default drive cycles. While the user can input average speeds in running MOVES,
that representation would be similar to MOBILE which was limited to using
average speeds to reflect vehicle activity. MOVES is more advanced in that it
will accept link drive schedules (vehicle trajectories) or operating mode
distributions (which represents processed link drive schedules). There is a
need to define links in a way that captures the most congested speeds. However,
there is no readily available reference for the user to generate this input and
take full advantage of this new advanced modeling capability provided by the
MOVES model.


For projects with significantly greater potential
impact or controversy, for which an environmental impact statement may be
prepared, even more refined approaches may be considered subject to any
limitations on project resources and schedule. For example, there is some
potential for using advanced traffic microsimulation models to generate vehicle
trajectories which can be transformed into link drive schedules. However there
are no defined tools or procedures for completing that conversion and results
are more related to individual vehicles and not a general trend. Furthermore,
traffic analysts have not validated the simulation models for vehicle
trajectories. Validation of the simulation models is a separate but related
task that is also being studied further. In addition, it might be beneficial to
provide guidance on adaptions of regional transportation modeling data for use
at the project level. The ability to better characterize truck and bus activity
with better data and modeling approaches is also of particular interest.


Going beyond the fundamental on-road
considerations, other details of the modeling process could benefit from
uniform guidance. This would include information on typical off-road operations
(e.g., intermodal activity with vehicle starts and bus dwell times).
Furthermore, additional support in characterizing the vehicle mix would better
reflect the emissions impacts from critical vehicle types (e.g., diesel trucks
and buses when looking at PM emissions), particularly for refined analyses as
noted above. From a practical perspective, air quality analysts would also
benefit from the development of a standard template or form for requesting
traffic appropriate to the level of analyses needed from DOT or transportation
modeling staff.


While related research is being conducted, it
does not specifically address best practices or project-level air quality
analyses. NCHRP 25-38 is related to the current topic, but that effort is more
directly related to standard MOVES inputs, including those for regional
analyses. This research would consider broader data issues, such as an
understanding of traffic operations in light of air quality implications. This
topic would also be broader in that it will consider analyses required to
satisfy the National Environmental Policy Act (NEPA), and not just conformity.
A final product might include a practical guide for analysts to use for a range
of studies, such as a Categorical Exclusion or Environmental Impact Statement
under NEPA or a hot-spot analysis to satisfy conformity.


Several earlier NCHRP studies (e.g., Reports
387 and 535) have dealt with related topics. However, these documents predate
the official release of MOVES and therefore do not fully address the modal
traffic inputs linked to this emissions model.


In addition to NCHRP 25-38, a number of areas
have initiated recent research into this topic (e.g., Vermont, Illinois, Texas,
FHWA/Volpe). But, consistency on a National basis and the ability to use these
results in a generic fashion are still lacking.


The overall objective of this research would
be to develop a practical guide if not best practices for the development of
travel data and forecasts (including specifically truck and bus data and
forecasts) for project level air quality analyses appropriate to the level of
NEPA study and needs for conformity where applicable. The primary intent is to
improve the traffic modeling inputs used for emission modeling, specifically
MOVES, and in doing so help to improve and streamline the project-level
analyses process consistent with federal requirements specified in MAP-21 and
the federal Every Day Counts Initiative.


The following list suggests potential tasks
for this research topic:


•             Evaluation
of simulation models and how these models could be used in determining correct
input for MOVES.

•             Determination
of a series of inputs in a generic sense for different facility types and at
intersections applicable for different NEPA and conformity purposes.

•             Identification
of consistent, reliable sources for truck and bus data, including guidance on
defining off-network activity.

•             Possible
suggested changes to the MOVES model.

•             Completion
of a final report incorporating these findings.


Ultimately, the effort would result in a
handbook or practical guidance for developing traffic inputs for project-level
air quality modeling.

Urgency and Payoff

The project would advance the state of the
practice for traffic forecasting to improve and streamline project-level air
quality analyses, consistent with federal requirements specified in MAP-21 and
the Every Day Counts initiative. The benefits include a streamlined process
that allows consistency in analysis from state-to-state and
location-to-location, cost savings (time and resources) by guiding modelers to
the appropriate level of analysis to meet regulatory requirements, and greater
accuracy in predictions which in turn allows for a more effective decision
making process.


These regulatory requirements were mandated
effective December 2012 and there is a steep learning curve, including new or
modified modeling tools and procedures. A recently completed regional level
sensitivity study on MOVES by FHWA/Volpe (ref) showed that use of defaults and
average speed can lead to variability in emission modeling.  While the differences are now being reviewed
in more detail in a project-level study, the need for real travel activity
input data still exists. Funding and multi-million dollar decisions depend on
the accurate modeling for mobile sources and the large source of error from
incorrect traffic input needs  work to
provide the air quality analyst with generic project level tools that allow for
better traffic input in terms of drive cycles and/or operating modes.



This research topic was listed as the highest
priority by the Project-Level Subcommittee of the TRB Transportation and Air
Quality (ADC20) Committee. Among those actively supporting this submission are:


Voigt, Virginia DOT (Subcommittee Chair)

Michael Claggett, FHWA Resource Center

Ploch, Texas DOT

Roger Wayson, RITA Volpe Center

Suggested By

Paul Heishman, PE FHWA Resource Center (for Project-Level Subcommittee of ADC20)

[email protected]