Smokelyze.org: Advanced Spatiotemporal Analytics for Wildfire Smoke and Air Quality

Abstract Wildfire smoke is drastically altering the air quality landscape across the United States (US), forcing environmental agencies to confront frequent exceedances of the National Ambient Air Quality Standards (NAAQS). Currently, the operational workflow for developing an Exceptional Event Demonstration (EED) is a resource-intensive process requiring disparate data portals and specialized software. This makes it challenging for state and federal agencies to demonstrate the relationship between smoke and air pollution. Additionally, few tools exist for health scientists to rigorously assess the PM 2.5 and O 3 impacts of wildfire smoke. To meet this need, we developed “Smokelyze”, an open-access, web-based app. Based on peer-reviewed research, it integrates surface observations, satellite data, meteorological data combined with machine learning (Generalized Additive Models or GAMs) to quantify smoke contributions to PM 2.5 and O 3 at nearly every regulatory monitor in all states. The app features a user-friendly workspace for visualizing the results, with fusion of our GAMs with multiple surface, satellite and transport parameters, including EPA’s AirNow monitoring data, NOAA HMS smoke polygons and fire locations, NASA’s TEMPO and TROPOMI for NO 2 and HCHO retrievals, and on-demand cloud-based HYSPLIT model results. Smokelyze provides an optimized environment for environmental agencies to understand and quantify the degree to which wildfire smoke influences PM 2.5 and O 3 . This understanding can be used to support state efforts to build EEDs. Smokelyze also provides a consistent tool to quantify surface smoke for health researchers, and democratizes complex atmospheric analyses and transforms static academic methodologies into an accessible, rapid verification product.