This research investigates atmospheric trace elements as indicators of pollution sources, focusing on toxic metal emissions from urban firestorms during the Eaton Canyon and Palisades fires. Elevated airborne lead concentrations prompted the creation of Phoenix, a community-based post-fire air monitoring network designed to track hazardous dust resuspension during debris cleanup.

Lead contamination in drinking water threatens millions. This research combines physics-based pipe models with machine learning to identify lead pipes using vibration data. Generating thousands of simulated signals enabled a classifier with 99% accuracy, offering a noninvasive, cost-effective method to locate hidden lead pipes and support safer water infrastructure worldwide.