State departments of transportation (DOTs) conduct project-level air quality analyses to conform to the National Environmental Policy Act (NEPA) and meet transportation conformity rule requirements where applicable. DOTs are interested in a rigorous and systematic model review and update process for regulatory dispersion models for the transportation sector to ensure that the models generate credible results.
In this context, the Airport Cooperative Research Program (ACRP) Report 71, Guidance for Quantifying the Contribution of Airport Emissions to Local Air Quality, provides information on modeling assessments and is a helpful reference. Another key reference is the 2007 National Research Council (NRC) report, Models in Environmental Regulatory Decision-Making, which called for consideration of multiple criteria for model assessments.
Building on ACRP Report 71, the 2007 NRC report, and other studies, DOTs would benefit from additional research that comprehensively examines project-level air quality dispersion models and assesses their respective strengths and weakness.
The objective of this research is to produce a technical report for decision makers to identify the appropriate air quality dispersion models for regulatory applications in the transportation sector. The technical report should: (1) specify procedures to test air quality dispersion models using real-world air quality data (which must include data from tracer studies) for regulatory applications in the transportation sector for criteria pollutants typically assessed in project level analysis; (2) apply these procedures to conduct detailed evaluation of the selected models against air quality field data; (3) based on the results of the analyses, evaluate the strengths and weaknesses of dispersion models for specific transportation regulatory applications for each pollutant; (4) present comparative analyses (including technical and methodological evaluations) to provide insights into why a particular model is the best performing model for those specific transportation applications; and (5) make recommendations for model improvements based on the model assessments and comparative analyses.