Electrification is considered a promising solution to environmental sustainability due to the removal of tailpipe emissions (during operation) from the transportation sector. However, this would not have a significant effect on non-tailpipe particulate emissions. In addition, brake and tire wear particles are composed of various metals, rubber compounds, and organics which includes adhesives and have potential higher risks on community health effects. In this study, the research team will: 1) measure real-world brake activities of a large volume of vehicles traversing major roadway segments (e.g., near signalized intersections) by leveraging advanced roadside sensing technologies, e.g., Light Detection and Ranging and/or high-definition camera, as well as deep learning-based computer vision algorithms; and 2) construct the real-world brake activity database and supplement for the non-tailpipe emissions inventory. It is expected that this study will contribute to the improvement of non-tailpipe emissions modeling and understanding. The findings from this study will help address environmental justice issues in disadvantaged communities.
