Research Idea Details

AI for QA/QC of EPA models

  • Focus Area: Air Quality
  • Status: Current
  • Subcommittee: Air Quality
  • Cost: $250k-$499k
  • Timeframe: 1-2 years

Research Idea Scope

This study would identify and test the potential use of AI to conduct quality assurance and quality control (QA/QC) for emission and dispersion models used in project-level air quality analyses for NEPA and conformity. For this purpose, this study would:

  • Identify candidate AIs and their pros and cons,
  • Conduct pilot assessments of the emission and dispersion models for algorithmic or coding errors or issues that could potentially affect modeling results,
  • Develop conclusions and recommendations for the application of AI for QA/QC purposes for emission and dispersion models. The recommendations may include suggested improvements to the models to address any identified errors or other issues.

Urgency and Payoff

State DOTs rely upon emission and dispersion models for project-level air quality analyses for NEPA and conformity for projects worth collectively billions of dollars. They would benefit from an AI tool that could be used to check and confirm that the models are reliable and free from significant errors, particularly when new or updated models are released.

Suggested By:
Christopher Voigt
[email protected]
Submitted:
09/22/2026