Fangjun Li

Fangjun Li is an Assistant Research Professor in the Department of Geography and Geospatial Sciences at the University of South Dakota. His research focuses on wildfire emissions modeling, air quality forecasting, and the application of satellite remote sensing technologies. Li specializes in integrating geostationary and polar-orbiting satellite data to estimate biomass burning emissions and improve operational weather-prediction systems. His work contributes to NOAA's efforts in developing high-resolution smoke simulation frameworks and enhancing the accuracy of fire-related air quality forecasts.

Li's research interests include fire seasonality analysis, machine learning-driven emission prediction, and the climatic impacts of wildfires. He has collaborated on projects such as the Unified Forecast System (UFS) and the FIREX-AQ field campaign, advancing methodologies for fire radiative power estimation and smoke plume modeling. His studies address critical issues like the record-breaking 2023 Canadian wildfires and long-term trends in grassland productivity linked to soil moisture variability.

Key achievements include developing the Global Biomass Burning Emissions Product (GBBEPx) and evaluating advanced plume rise schemes to mitigate PM2.5 exceedances during extreme wildfire events. Li’s work bridges environmental science, atmospheric modeling, and operational forecasting, with implications for disaster management and climate policy.