Towards science-driven designs of transportation green infrastructure

Cornell University, Ithaca NY

Investigators

Abstract

1605407 Zhang Near-road air pollution is a worldwide public health concern. A predictive tool (model) will be developed to analyze various atmospheric processes and their interactions in the roadway-vegetation environments. The overall research objective of this proposal is to test the hypothesis that science-driven designs of roadside green infrastructure such as vegetation barriers and vegetated noise barriers can effectively mitigate near-road air pollution. The predictive tool will be built on an environmental turbulent reacting flow modeling framework, Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry, developed by PI's research group. New components will be created to represent the turbulent mixing and atmospheric deposition processes due to roadside green infrastructure. In addition, a full gas-phase chemical mechanism will be incorporated to assess the role of biogenic volatile organic compound emissions on near-road air pollution. Furthermore, a novel method to couple turbulent mixing and multi-component aerosol dynamics will be created to enhance the accuracy in quantifying the effects of green infrastructure on evolution of particulate matter near roadways. Each process will be tested extensively against both laboratory and field measurement datasets. Working with ecosystem designers and scientists, the research team will apply the predictive tool to investigate how the advanced scientific understanding can improve real-world green infrastructure designs, i.e., testing the hypothesis, at two locations, Oakland, CA and Research Triangle Park, NC. Finally, the effects of green infrastructure will be parameterized by modifying Gaussian plume formulations using a novel multi-regime method based on the fundamental understanding of the flow structures before and behind roadside green infrastructure. The parameterizations will be incorporated into a highway dispersion model, CALINE4. Thus the modified CALINE4 becomes an assessment tool for the broad community. The specific objectives of the proposed project are to: 1) elucidate how the presence of green infrastructure affects the different atmospheric processes near roadways using an integrated experimental modeling approach, 2) evaluate how different green infrastructure designs affect their effectiveness in reducing near-road air pollutant levels, and, 3) create an assessment tool that allow planners and designers to evaluate different green infrastructure designs. The research products from this project will transform the transportation planning and community designing process. The current role of transportation planning in improving air quality is mostly "passive," meaning that air quality is treated as compliance. The research will encourage local communities to identify solutions to their local near-road air pollution problems, contributing to sustainable community development. Their modeling framework will become a platform for fostering interdisciplinary partnerships among different fields (e.g., air quality and transportation management, landscaping and urban planning) in solving transportation air quality problems. The collaborations with government agencies (i.e., EPA and Forestry Service), companies (i.e., Accent Environmental) and NGOs (i.e., Urban Biofilter and Breathe California of Sacramento) on this project will mark the first step towards this interdisciplinary partnership. Lastly, the objective of the education plan is to bring more underrepresented minority students into the research fields, built on PI's previous success in working with and recruiting underrepresented minority students. Besides the interdisciplinary training of a graduate student, the PI will partner with the Diversity Programs in Engineering at Cornell University to recruit underrepresented minority undergraduates to work on the Research Experiences for Undergraduates (REU) program associated with the proposed project.