RESUMEN
Emissions from a stand replacement prescribed burn were sampled using an unmanned aircraft system (UAS, or "drone") in Fishlake National Forest, Utah, U.S.A. Sixteen flights over three days in June 2019 provided emission factors for a broad range of compounds including carbon monoxide (CO), carbon dioxide (CO2), nitric oxide (NO), nitrogen oxide (NO2), particulate matter < 2.5 microns in diameter (PM2.5), volatile organic compounds (VOCs) including carbonyls, black carbon, and elemental/organic carbon. To our knowledge, this is the first UAS-based emission sampling for a fire of this magnitude, including both slash pile and crown fires resulting in wildfire-like conditions. The burns consisted of drip torch ignitions as well as ground-mobile and aerial helicopter ignitions of large stands comprising over 1,000 ha, allowing for comparison of same-species emission factors burned under different conditions. The use of a UAS for emission sampling minimizes risk to personnel and equipment, allowing flexibility in sampling location and ensuring capture of representative, fresh smoke constituents. PM2.5 emission factors varied 5-fold and, like most pollutants, varied inversely with combustion efficiency resulting in lower emission factors from the slash piles than the crown fires.
RESUMEN
PM2.5, or fine particulate matter, is a category of air pollutant consisting of particles with effective aerodynamic diameter equal to or less than 2.5 µm. These particles have been linked to human health impacts as well as regional haze, visibility, and climate change issues. Due to cost and space restrictions, the U.S. Environmental Protection Agency monitoring network remains spatially sparse. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations, despite these estimates being associated with moderate to large uncertainties when relating a column measure of aerosol (aerosol optical depth) with surface measurements. To this end, we discuss a low-cost air quality monitor (LCAQM) network deployed in California. In this study, we present an application of LCAQM and satellite data for quantifying the impact of wildfires in California during October 2017. The impacts of fires on PM2.5 concentration at varying temporal (hourly, daily, and weekly) and spatial (local to regional) scales have been evaluated. Comparison between low-cost air quality sensors and reference-grade air quality instruments shows expected performance with moderate to high uncertainties. The LCAQM measurements, in the absence of federal equivalent method data, were also found to be very useful in developing statistical models to convert aerosol optical depth into PM2.5 with performance of satellite-derived PM2.5, similar to that obtained using the federal equivalent method data. This paper also highlights challenges associated with both LCAQM and satellite-based PM2.5 measurements, which require further investigation and research.