(269b) Integrated Approach to Explore Roadway Air Impact of Travel Demand and Traffic Operation for Transportation Sustainability Analysis

Sustainable and green urban growth highly needs the ability to measure and forecast carbon footprint that may be reflected by analyzing sensitive interactions between travel demand due to adaptive changes in land use and social economy and the impact of transportation activities on road emission and ambient air quality. Advanced traffic management, operation, and control technologies and systems have generated considerable enthusiasm in the transportation community as a potential strategy for reducing highway congestion and environmental impacts associated with vehicle travel. The U.S transportation conformity program requires transportation plans, programs, and projects to “confirm to” the goals established in statewide transportation improvement programs (STIP). Meanwhile, transportation activities must ensure not cause new air quality violations, or worsen existing violations, or delay timely attainment of the National Ambient Air Quality Standards (NAAQS) for traffic-generated air pollutants. Therefore, methodologies are needed to enable the above capabilities tangible and practical.  

This paper presents a framework to fill in this gap through developing the Geographical Information System (GIS)-based Roadway Air Impact Analysis (RAIA) system, housed in the Scenario-Based Planning Support System (SB-PSS) system. This RAIA system is established using an integrated approach, i.e., categorized models, namely, travel forecasting model, vehicle emission model, and vehicle powered energy consumption model, are integrated heuristically and mathematically with data flows via input/output (I/O) interfaces. Additionally, the air quality index based on NAAQS (National and State of Ambient Air Quality Standards) will be embedded into the GIS environment.  Travel demand forecasting models estimate the trips based on land use adaptation and social economic fabric; micro traffic simulation model is used to assess the measures of effectiveness of traffic operation and control strategies; vehicle emission model estimates the emission factors due to transportation activities; and vehicle powered energy consumption model is used to estimate energy consumption. Within this environment, traffic-related emission and energy consumption demand will be forecasted based on various scenarios with the addressed factors. Such an integration effort will be greatly beneficial to identifying strategic solutions to design and operate transportation systems in a way that meets transportation needs while protecting the environmental health of all people, and provides supportive information for measuring and assessing sustainability and “greenness” of transportation systems.

Three main layers are involved in the system, namely, data layer, scenario interactive analysis layer, and assumptions layer. The data layer receive, store and manipulate all the data that will be resulted from either the procedure of simulation environmental analysis. It is expected to enable inputting and storing the outputs from macro- and micro- traffic simulation models into the integrated system. Assumptions layer sets up assumptions for specifying suitability of a scenario versus concerned assessment criteria within the impact analysis system. The user has the ability to modify this assumption and dynamically view the differing outcome that results. Assumptions give the user to specify data querying criteria and threshold values. Criteria for setting up scenarios (e.g., assumptions, dynamic attributes, and indicators like NAAQS) are manifested by user-defined values and formulas that relate one component to another. Regression models for school-age population exposure levels to air pollution will be used to enhance the function for display of “black spots.”  Finally, a case study of CO and Black Carbon monitoring along with traffic observation at I-75 highway in Cincinnati, Ohio, will be used to present a proposed procedure of validating traffic simulation applied with emission models.