Assessment of the State-of-the-Practice of Model Improvement Programs for Air Quality Regulatory Models
Research Idea Scope
In 2007, the National Research Council (NRC) issued the landmark report “Models in Environmental Regulatory Decision Making” (http://www.nap.edu/catalog/11972/models-in-environmental-regulatory-decision-making). It assessed EPA’s use of computer models in developing regulations and recommended a series of guidelines and principles for improving agency models and decision-making processes. Given the long duration in service (decades) of EPA models, a periodic review and update process involving key stakeholders (including state DOTs) is needed to ensure that the models continue to meet regulatory needs with requisite accuracy and are efficient and cost-effective to apply. This proposed study would apply the 2007 NRC report (for the first time) to the project-level modeling chain (traffic, emission and dispersion) for transportation projects and develop recommendations for model improvement programs (MIPs) or improved processes. To the extent resources permit, this study would also address regional emission modeling for inventory purposes.
More specifically, this proposed study would apply the concepts presented in the 2007 NRC report to:
* assess the review and update processes currently in place for the models used in project-level air quality analyses as well as the overall modeling chain,
* identify any deficiencies in the processes, and
* make recommendations for improvements as appropriate.
For background, the National Academies Press provides the following description for the 2007 NRC report: “Many regulations issued by the U.S. Environmental Protection Agency (EPA) are based on the results of computer models. Models help EPA explain environmental phenomena in settings where direct observations are limited or unavailable, and anticipate the effects of agency policies on the environment, human health and the economy. Given the critical role played by models, the EPA asked the National Research Council to assess scientific issues related to the agency’s selection and use of models in its decisions. The book recommends a series of guidelines and principles for improving agency models and decision-making processes. The centerpiece of the book’s recommended vision is a life-cycle approach to model evaluation which includes peer review, corroboration of results, and other activities. This will enhance the agency’s ability to respond to requirements from a 2001 law on information quality and improve policy development and implementation.”
Overall, the scope would include consideration of:
* Traffic/activity, emission and dispersion modeling as applicable for each pollutant and project type.
* A range of typical highway, transit and inter-modal/off-network project types.
* Regulatory requirements and guidance for both NEPA and the EPA transportation conformity rule.
* Pollutants typically addressed in project-level modeling, including carbon monoxide (CO), particulate matter (PM2.5 and PM10), and mobile source air toxics (MSATs). Greenhouses gases may also be addressed as appropriate, following the pending release of guidance for NEPA analyses from FHWA.
Tasks may include:
1. Document the relevance of the 2007 NRC report to project-level modeling for transportation, which generally includes traffic/activity, emission and dispersion modeling as well as the overall modeling chain. It also includes construction emissions. To the extent that resources permit, address regional modeling, which includes traffic and emission modeling as well as the overall modeling chain.
2. Identify key elements of a formal review and update process (model improvement program) that would be recommended for project level modeling based on the concepts presented in the 2007 NRC report. Key elements may include:
a. Periodic review and update processes, e.g., every 5 years
b. Open and transparent consultation process, with consultation involving key stakeholders including transportation (US DOT, state DOTs, industry etc.) that would have access to all data and information used in the review and update process
c. Priorities for model and modeling process improvements established for the next five year period (strategic planning concept) based on:
i. Assessments of model performance for:
* Accuracy: Evaluations of the models and overall modeling chain against field data (e.g., traffic and ambient air quality data) for various typical transportation projects, configurations and operation conditions (highways, transit, intermodal), etc.
* Efficiency: Sensitivity assessments of the costs and contribution of each model input to the accuracy and uncertainty of output of each model and the overall modeling chain.
* Appropriateness to the regulatory need, including both how accurate and how precise the models need to be for project-level analyses in order to meet specific regulatory requirements and how uncertainty should be addressed in the analyses and in the reporting of results (including what analyses would be needed to appropriately quantify uncertainty and how the results should be understood and reported in order to support or improve the overall decision making process).
ii. Surveys of stakeholders for feedback on model performance, features, costs, data requirements etc.
iii. Other factors
3. Assess the current state of the practice of the review and update processes for each model (and the overall modeling chain) against the elements or criteria identified in the previous task.
a. Traffic/Activity. Note FHWA has a Travel Modeling Improvement Program (TMIP) for regional modeling issues already in place: http://www.fhwa.dot.gov/planning/tmip/
b. Emissions (MOVES/EMFAC, and construction). Note MOVES has (or had) a model improvement process that may largely meet the intent of the 2007 NRC report and may just need to be established as an ongoing program with any refinements that this study might identify. This study may also address how the current MOVES model satisfies the recommendations of the 2000 NRC report on “Modeling Mobile Source Emissions” (http://www.nap.edu/catalog/ 9857/modeling-mobile-source-emissions) that led to its creation and, more to the point, how its MIP should be structured.
c. Dispersion (CAL3QHC, CAL3QHCR, AERMOD), for which MIPs with state DOT involvement would be desirable. Note this assessment would be expected to include a review of the extent to which dispersion models have (or have not) been evaluated against ambient data for typical highway, transit and inter-modal project types, configurations and operating conditions.
d. Overall Modeling Chain, for which a MIP with state DOT involvement would be desirable.
4. Conclusions and Recommendations
a. Recommendations for model improvement programs for each model and the overall modeling chain, including the specification of key elements for each MIP (which may be met by existing programs to varying degrees)
b. Priorities for future research/phases based on the assessments of the current processes, including regional modeling.
Urgency and Payoff
State DOTs and other agencies working on transportation-related air quality issues are under financial and environmental constraints more than any other time in recent history. This project is designed to improve the credibility and reliability of the air quality impact analysis process. An improved process for conducting this analysis should ultimately reduce environmental challenges which result in extended project completion times and costs. Overall, state DOTs would benefit from the implementation and/or refinement of model improvement programs (MIPs) that lead to models with greater accuracy (and less uncertainty) for typical highway, transit and inter-modal projects, be more cost-effective to apply, and reduce litigation risk. This project was identified as a priority project in the 2015 Annual Meeting of the Project-Level Analysis Subcommittee of the TRB Transportation and Air Quality Committee (ADC20). The proposal research topic was developed by John Koupal, Christopher Voigt and Kevin Black.
John Koupal Eastern Research Group, Inc 508-868-0786