We conducted a 2-year study utilizing a network of fixed sites with sampling throughout an extended prescribed burning period to characterize the emissions and evolution of smoke from silvicultural prescribed burning at a military base in the southeastern USA. The measurement approach and an assessment of the instrument performance are described. Smoke sources, including those within and off the base, are identified, and plume ages are determined to quantify emissions and study the evolution of smoke PM_2.5 (particulate matter with aerodynamic diameters 2.5 µm or smaller) mass, black carbon (BC), and brown carbon (BrC). Over the 2021 and 2022 prescribed burning seasons (nominally January to May), we identified 64 smoke events based on high levels of PM_2.5 mass, BC, BrC, and carbon monoxide (CO), of which 61 were linked to a specific burning area. Smoke transport times were estimated in two ways: using the mean wind speed and the distance between the fire and the measurement site, and from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectories. PM_2.5 emission ratios based on ΔPM_2.5 mass $/$ ΔCO for fresh smoke (age ≤ 1 h) ranged between 0.04 and 0.18 µg m⁻³ ppb⁻¹ with a mean of 0.117 µg m⁻³ ppb⁻¹ (median of 0.121 µg m⁻³ ppb⁻¹). Both the mean emission ratio and the variability were similar to findings from other prescribed fire studies but were lower than those from wildfires. The mean emission ratios of BC and BrC were 0.014 µg m⁻³ ppb⁻¹ and 0.442 Mm⁻¹ ppb⁻¹, respectively. Ozone enhancements (ΔO₃) were always observed in plumes detected in the afternoon. ΔPM_2.5 mass $/$ ΔCO was observed to increase with plume age in all of the ozone-enhanced plumes, suggesting photochemical secondary aerosol formation. In contrast, ΔBrC/ΔCO was not found to vary with plume ages less than 8 h during photochemically active periods.

Prescribed burning is a major source of a fine particular matter, especially in the southeastern United States, and quantifying emissions from burning operations accurately is an integral part of ascertaining air quality impacts. For instance, a critical factor in calculating fire emissions is identifying fire activity information (e.g., location, date/time, fire type, and area burned) and prior estimations of prescribed fire activity used for calculating emissions have either used burn permit records or satellite-based remote sensing products. While burn permit records kept by state agencies are a reliable source, they are not always available or readily accessible. Satellite-based remote sensing products are currently used to fill the data gaps, especially in regional studies; however, they cannot differentiate prescribed burns from the other types of fires. In this study, we developed novel algorithms to distinguish prescribed burns from wildfires and agricultural burns in a satellite-derived product, Fire INventory from NCAR (FINN). We matched and compared the burned areas from permit records and FINN at various spatial scales: individual fire level, 4 km grid level, and state level. The methods developed in this study are readily usable for differentiating burn type, matching and comparing the burned area between two datasets at various resolutions, and estimating prescribed burn emissions. The results showed that burned areas from permits and FINN have a weak correlation at the individual fire level, while the correlation is much higher for the 4 km grid and state levels. Since matching at the 4 km grid level showed a relatively higher correlation and chemical transport models typically use grid-based emissions, we used the linear regression relationship between FINN and permit burned areas at the grid level to adjust FINN burned areas. This adjustment resulted in a reduction in FINN-burned areas by 34%. The adjusted burned area was then used as input to the BlueSky Smoke Modeling Framework to provide long-term, three-dimensional prescribed burning emissions for the southeastern United States. In this study, we also compared emissions from different methods (FINN or BlueSky) and different data sources (adjusted FINN or permits) to evaluate uncertainties of our emission estimation. The comparison results showed the impacts of the burned area, method, and data source on prescribed burning emission estimations.

Prescribed burning is an effective land management tool that provides a range of benefits, including ecosystem restoration and wildfire risk reduction. However, prescribed fires, just like wildfires, introduce smoke that degrades air quality. Furthermore, while prescribed fires help manage wildfire risk, they do not eliminate the possibility of wildfires. It is therefore important to also evaluate fire and smoke impacts from wildfires that may occur after a prescribed burn. In this study, we developed a framework for understanding the air quality and health related trade-offs between wildfires and prescribed fires by simulating a set of counterfactual scenarios including wildfires, prescribed fires, and postprescribed burn wildfires. We applied this framework to the case of the Gatlinburg wildfire and found that emissions from prescribed burns and subsequent wildfire were slightly lower than those from the wildfire itself. This reduction resulted in lower daily average concentrations and exposures of PM_2.5, O₃, and NO₂. Even considering the possibility of a postprescribed burn wildfire, prescribed fires reduced population-weighted daily average PM_2.5, daily maximum 8-h average O₃, and 1-h maximum NO₂ concentrations. In Sevier County, Tennessee where the wildfire occurred, these reductions reached 5.28 μg/m³, 0.18 ppb, and 1.68 ppb, respectively. The prescribed fires also reduced the person-days smoke exposures from the wildfire. Our results suggest that although prescribed fires cannot eliminate the air quality impacts of wildfires, they can greatly reduce smoke exposure in downwind areas distant from the burn sites.