The National Academies

NCHRP 25-25/Task 96 [Pending]

Quick Reference Guide for Traffic Modelers for Generating Traffic and Activity Data for Project-Level Air Quality Analyses
[ NCHRP 25-25 (Research for the AASHTO Standing Committee on the Environment) ]

  Project Data
Funds: $75,000
Contract Time: 12 months
Staff Responsibility: Lori Sundstrom


There is a frequent disconnect between the traffic data needed for project-level air quality analysis and the traffic data provided by traffic modelers.  The disconnect leads to waste in processing and time and introduces project risk by introducing uncertainty into the NEPA and Transportation Conformity process. The challenge stems from different technical vocabulary and knowledge-base of air quality and transportation modelers.  State DOTs need guidance that can bridge the gap between air quality and traffic modelers by articulating air quality needs with an understanding of common language and tools available to traffic modelers.  The purpose is not to create a new process for AQ but to improve communication between disciplines and build upon the recently completed NCHRP project 25-38, “Input Guidelines for Motor Vehicle Emissions Simulator Model”.


Research Objective:

The objective of this research is to supplement the recently completed NCHRP Report 765, "Analytical Travel Forecasting Approaches for Project-Level Planning and Design" by providing guidance focusing specifically on generating traffic information for air quality analysis.  This research this effort will aid traffic modelers in understanding the traffic data needed for air quality analysis and contribute to improved accuracy and efficiency of the traffic and activity modeling that is necessary to complete federally required air quality analysis by providing guidance to modelers to help them develop data in format that can be easily used by air quality analysts.  NCHRP Report 765 addressed the general subject of project-level modeling in detail but does not address needs specific to project-level air quality analyses.

The amount and complexity of air quality data needs varies by location, modal components, pollutant, context (e.g., stakeholder concerns). Guidance would need to consider all these variables along with traffic data considerations for when air quality mitigation includes operational changes to traffic.

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