Development of a Data-Driven Analytical Framework to Assess Air Quality Impacts of Transportation Projects
Research Idea Scope
To comply with the transportation conformity requirements, state and local transportation agencies use various transportation strategies designed to reduce air pollutant emissions in nonattainment and maintenance areas by improving traffic flow and/or reducing vehicle use. FHWA’s Congestion Mitigation and Air Quality (CMAQ) Improvement Program is an important source of funding for these projects. Under the MAP-21 the state DOTs and MPOs are directed to give priority to cost-effective projects when applying for CMAQ funding. Emissions reduction benefits is one of the key parameter in determining the cost-effectiveness of a transportation project. Uncertainty in emissions estimates has been identified as one of the major limitations of current cost-effectiveness estimates. The current emission estimation methodologies used for CMAQ-funded projects are usually aggregate methods that are not highly sophisticated and often do not account for local traffic information. Furthermore, these estimates are developed before the implementation of the project and no follow-up studies are done to validate the assumptions and results. Lack of this information (i.e. before- and after-implementation studies) has remained a major contributor to the uncertainty with the emission estimation and cost-effectiveness of CMAQ projects. Research is needed to improve the accuracy of the methods and assumptions used for emissions analyses based on real-world data. The emergence of non-traditional traffic datasets, such as National Performance Management Research Data Set (NPMRDS), state funded data collection, and INRIX database, which contain fine-scale traffic activity information has provided an opportunity to potentially improve the project-level emission estimation methodologies and the accuracy of the air quality impact estimates. These outcomes are crucial to improve transportation agencies’ project selection process based on more realistic estimates of the cost-effectiveness and emissions reduction benefit of potential transportation projects.
Urgency and Payoff
Lack of proper methodologies has limited the use of fine-scale traffic data in transportation air quality analyses. This project will assist sate DOTs and MPOs on improving their CMAQ project selection decision making with the aim of maximizing the benefits to the tax payers in the form of improved air quality. Sometimes there are not enough CMAQ-qualified projects selected and submitted for CMAQ funding by MPOs, which results in underutilization of CMAQ resources allocated to the state. The findings of this research will help MPOs and DOTs to make sure that all CMAQ resources are utilized optimally. In summary, this project will help better project selection decision making by transportation agencies through the use of more realistic and accurate estimates of the cost-effectiveness and emissions reduction benefit of potential transportation projects.
Madhusudhan venugopal Texas A&M Transportation Institute