Fire emission uncertainties and their effect on smoke dispersion predictions: a case study at Eglin Air Force Base, Florida, USA

Abstract

Prescribed burning is practiced to benefit ecosystems but the resulting emissions can adversely affect air quality. A better understanding of the uncertainties in emission estimates and how these uncertainties affect smoke predictions is critical for model-based decision making. This study examined uncertainties associated with estimating fire emissions and how they affected smoke concentrations downwind from a prescribed burn that was conducted at Eglin Air Force Base in Florida, US. Estimated variables used in the modelled emission calculation were compared with field measurements. Fuel loadings, fuel consumption and emission factors were simulated using Photo Series, Consume, and previously published values. A plume dispersion model was used to study the effect of uncertainty in emissions on ground concentration prediction. The fire emission models predicted fuel loading, fuel consumption and emission factor within 15% of measurements. Approximately 18% uncertainty in field measurements of PM 2.5 emissions and 36% uncertainty attributed to variability in emission estimating models resulted respectively in 20% and 42% ground level PM 2.5 concentration uncertainties in dispersion modelling using Daysmoke. Uncertainty in input emissions influences the concentrations predicted by the smoke dispersion model to the same degree as does the model's inherent uncertainty due to turbulence.

The Impacts of Prescribed Fire on PM2.5 Air Quality and Human Health: Application to Asthma-Related Emergency Room Visits in Georgia, USA

“…Besides the uncertainty in β, there are other uncertainties in estimating the prescribed burning related health impact. Previous studies show that the measured PM 2.5 emissions from prescribed burning is about 90% of modeled emissions [34]. Using the BlueSky framework (as done here), the PM 2.5 emissions we estimated for the same case were about 60% of measured emissions.…”

Black carbon aerosol dynamics and isotopic composition in Alaska linked with boreal fire emissions and depth of burn in organic soils

“…Bottom-up model estimates of carbon emissions are uncertain because of challenges in modeling fuel loads and depth of burn (and thus fuel consumption) in organic soil layers of boreal forests [French, 2004;Soja, 2004;Turetsky et al, 2010;Rogers et al, 2014;Veraverbeke et al, 2015]. Emission factors of BC production per unit of combusted biomass are known to vary as a function of fuel type, fuel moisture content, and flaming versus smoldering combustion phases, further increasing the range of possible estimates [Reid et al, 2005;Koch et al, 2009;Akagi et al, 2011;French et al, 2011;Bond et al, 2013;Yokelson et al, 2013;Kukavskaya et al, 2013;Davis et al, 2015]. Within the atmosphere, additional uncertainties are introduced from difficulties in simulating BC aging, atmospheric transport, and rates of dry and wet deposition [Croft et al, 2005;Koch et al, 2009;Xian et al, 2009;Vignati et al, 2010;Bond et al, 2013].…”

Forecasting the Impacts of Prescribed Fires for Dynamic Air Quality Management

“…Emission estimation starts with estimation of the fuel load and fuel consumption. A detailed description of the procedure used for emission estimation can be found in Davis et al [20]. We currently use the Fuel Characteristic Classification System (FCCS) fuel-bed maps to determine the fuel loads in burn locations assigned to each county.…”