Theoretical investigations on strategies for sampling meteorological and chemical field quantities in smoke plumes using UAVs

Abstract

Wildfires emit large quantities of pollutants that decrease the air quality in the atmospheric boundary layer. Understanding the chemical makeup of a fire plume is beneficial for air quality studies and for air quality forecasting in communities. To be able to understand the chemical composition, Unmanned Aerial Vehicles (UAVs) should be flown into plumes with an air quality instrumental payload. Before such flights can be completed it is crucial that the flight paths will allow for a complete understanding of the chemical concentration distributions within the plume. To develop such a flight path, with respect to flight altitude, direction and speed the UAV should travel at for examining a wildfire plume in Interior Alaska, output from the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) was used and was considered to be the true atmospheric conditions over the UAV measurement domain. For this thesis simulations were for 3-10 August 2009 of the Alaska fire season, centered in Interior Alaska. Focus for the UAV study was on the smoke plumes from the Crazy Mountain Complex fires near Circle, AK. Based on the results from the comparison of different flight altitudes, sampling patterns, and speeds of the simulated UAV flights, recommendations can be made for the use of UAVs in a field campaign into a wildfire plume in Interior Alaska.