Using Integrated Observations and Modeling to Better Understand Current and Future Air Quality Impacts of Wildfires and Prescribed Burns

Contact

Principal Investigator/Author: Michael Kleeman

Contractor: University of California, Davis

Contract number: 23RD006

Project Status: Active

Relevant CARB programs: Wildfire

Topic areas: Wildfires, Prescribed Burning, Climate Change

 

Research Summary:

Prescribed fire has been promoted as a tool for management of fire-resilient ecosystems and mitigation of risk for catastrophic wildfires. However, prescribed fires also have potentially significant consequences for air quality and public health. This is why scientific studies are needed to better understand the relative emissions, chemistry, and transport of smoke from wildfires versus prescribed burns. 

Researchers at the University of California, Davis (UCD) will quantify the relative magnitude and timing of pollutant emissions, extent of chemical transformation, transport and dispersion, and resulting toxicity of smoke from wildfires and prescribed burns. They plan to use a measurement-modeling approach that combines (1) a mobile measurement system developed for rapid deployment during fires and (2) a model that has been enhanced to predict dispersion and chemical transformation in smoke plumes. The models chosen for this project allow prediction of air pollutants including particulate matter and hazardous air pollutants at 1-24 kilometer resolution, which is an appropriate spatial scale to track the impacts of wildfires and prescribed burns on urban population centers in California. These measurements and modeling tools will be used to:

  • collect field samples measurements in at least two wildfires and prescribed burns over the next two years
  • simulate smoke exposure during all major wildfires in California over the past ten years and prescribed burn scenarios to mitigate wildfire risk
  • compare population exposure in wildfire and prescribed burn scenarios
  • compare predicted and measured concentrations in plumes downwind of wildfires and prescribed burns, and evaluate the model's ability to predict chemical aging of smoke

 

Keywords: wildfires, prescribed burns, wildfire risk, wildfire mitigation, smoke exposure, wildfire exposure, modeling, smoke emissions