Using an Unmanned Aerial Vehicle to Sample Aerosols in Wildfire Plumes
JOHN RYAN HIMES, Christian Carrico, Manvendra Dubey, Jon Reisner, New Mexico Institute of Mining and Technology
Abstract Number: 103
Working Group: Carbonaceous Aerosols
Abstract
The low-intensity ground-level fires necessary for forest health have increasingly been replaced by uncontrolled, crowning, and stand-replacing fires due to a warming climate and accumulated fuel loads. This not only has led to a substantial loss of land and livelihoods, but has also raised serious air quality concerns. Wildland fires emit significant amounts of particulate matter less than 2.5 micrometers in aerodynamic diameter (PM2.5) including black carbon (BC) and brown carbon (BrC) particles. The inhalation of PM2.5 has been known to cause numerous adverse health effects while BC and BrC hold their own climate-forcing potential and remain large uncertainties in climate models. Traditional ground-based air quality measurements are prone to missing a wildfire plume depending on wind direction and plume loft. Using a customizable unmanned aerial vehicle (UAV) to carry lightweight instrumentation provides a means to actively sample a wildfire plume and provide critical data for climate model validation. Two instrument types were utilized in initial UAV flights: a multiwavelength light absorption instrument (AethLabs MA200) and a light-scattering based mass concentration sensor (PurpleAir). Due to its recent inception, laboratory experiments were conducted to validate the PurpleAir. By aerosolizing liquid smoke, a good optical proxy for BrC, two Purple Air sensors were found to be well correlated to two QuantAQ modules (R2 > 0.98) and showed slope values of 0.8 to 1.2. Initial UAV flights were conducted at the Socorro Fire Training Center (SFTC) to sample emissions from burning buildings and diesel fuel spills; both of which are representative of fuels in the wildland-urban interface. The UAV system was able to detect distinct BC and BrC dominated regimes and transitions (determined by calculating the Absorption Ångström Exponent) as well as map gradients in PM2.5 concentrations from background to extremely high concentrations (>1300µg/m3).