SBIR Phase I: Ecosystem Design Tool

The broader impact of this SBIR Phase I project is to enable tools to inform methods to reduce air pollution. Air pollution increases the risk of cancer, stroke, heart disease, respiratory infections; further, it may play a role in Alzheimer's disease and diabetes, resulting in trillions of dollars of health care costs globally each year. Half of these costs may be attributed to roadway traffic sourced pollution. Traffic sourced pollution is possibly intercepted by trees, although improperly configured roadside trees do not produce these benefits and creating the opportunity for improved health via targeted engineering of roadside tree placements. This project will develop analysis and design tools to make sure that such tree plantings optimize benefits for ecosystem designers, health insurance companies, governments, and local businesses. This SBIR project will develop a system to optimize high-resolution site-specific tree placement for pollution reduction. Trees are known to reduce air pollution by acting like filters as their high surface area attracts pollutants. Tightly packed trees of a type with high surface area placed on the leeward side of a busy roadway can intercept > 30% of traffic sourced pollutants. This project will perform ground-based, high-resolution vegetation analysis on neighborhoods under study. These data will be used to train an algorithm to infer high-resolution vegetation properties from widely available, low-cost data streams. These inferred vegetation metrics will be integrated with a geospatial ecosystem design automation pipeline to create a software tool. To accurately predict the capture, high-resolution vegetation surface area measurements, tree crown spacing information, wind speed, wind direction and roadway traffic volumes will be aggregated in a comprehensive model. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.