Wildland fires emit a substantial amount of atmospheric pollutants including carbon monoxide (CO), methane (CH4), volatile organic compounds (VOC), nitrogen oxides (NOx), fine particulate matter (PM2.5), and black carbon particles (BC). These emissions have major impacts on local and regional air quality and global climate. In addition to being primary pollutants, the photochemical processing of NOx and VOC leads to the formation of ozone (O3) and secondary PM2.5. The most important criteria for assessing the impacts of fires on the regional and global environment are accurate, reliable information on the spatial and temporal distribution of fire emissions.
The chemical composition of smoke is quantified using emission factors. The emission factor for pollutant X quantifies the amount of X emitted per a unit mass of fuel burned. The total mass of pollutant X released by a wildland fire is calculated as the product of its emission factor, the area burned, and the fuel loading burned. Emission factors are critical inputs for atmosphere-chemical models used to forecast the impact of fire emissions on atmospheric composition, air quality, and climate. Emission factors are affected by vegetation type and combustion characteristics of a fire, in particular the amount of flaming and smoldering combustion. Some chemical species are emitted almost exclusively by flaming or smoldering, while the emissions of others are substantial from both processes. The combustion characteristics of wildland fires are believed to be influenced by several factors including: (1) fuel moisture, (2) the structure and arrangement of fuels, (3) fuel chemistry, (4) fuel growth stage and soundness of woody material, and (5) meteorology.
Fuel moisture and structure play an important role in the heating rate, ignition, consumption, and combustion completeness of wildland fuels. Figure 1 illustrates the general influence fuel bed properties on the combustion process and pollutant emissions. Fuel particles that are dry, small in size, and loosely packed favor flaming combustion. Fuel beds composed of particles that are moist, densely packed, or large in size favor smoldering combustion. In emissions research, the efficiency of the wildland fuel combustion process is assessed by the fraction of carbon in burned fuel that is released as CO2. Flaming combustion is more efficient than smoldering combustion - for each kilogram of fuel burned flaming produces more CO2 than smoldering. Compared with flaming combustion, smoldering releases more of the carbon in the burned fuel as incomplete combustion products such as PM2.5, CO, CH4, and VOC (i.e. something other than CO2). The more a fire smolders, the lower its combustion efficiency and the greater its production of harmful pollutants.
Some laboratory studies have reported a linkage between fuel moisture and emission factors. However, a robust relationship between emission factors and fuel moisture and/or fuel structure has not been demonstrated. Previous lab experiments have had several shortcomings: limited range of fuel moistures, insufficient replicates, and omission of fuel structure. This project seeks to address two key scientific questions:
- Are emission factors for CO2, CO, CH4, PM2.5, and particulate organic carbon (OC) and elemental carbon (EC) significantly dependent on either fuel moisture or fuel bed structure?
- Can fuel moisture and fuel bed structure serve as independent variables for empirical models that reliably predict these emission factors?
This project focused on a fuel bed composed of simple fuel particles — ponderosa pine needles (PPN). Ponderosa pine was selected because it contains a common fuel component, conifer needles, which can be easily arranged into fuel beds of variable structure (bulk density and depth) and moisture contents that are both representative of natural conditions and are easily replicated. Fuel bed bulk density is the mass of litter per unit volume; typical litter bulk densities are 25 kg m-3 for western Fir/Spruce, 50kg m-3 for Ponderosa Pine, and 85 kg m-3 for Loblolly Pine.
Three hypotheses were tested:
- The combustion efficiency of PPN litter decreases with increasing fuel bed bulk density.
- The combustion efficiency of PPN litter decrease with increasing fuel bed depth.
- The combustion efficiency of PPN litter decreases with increasing moisture content.
We discovered that, as expected, the combustion efficiency of PPN litter decreases as the fuel bed bulk density increases (Hypothesis 1). This resulted in increased emissions of CO, CH4, and PM2.5 (see Figure 2). However, fuel bed depth (whether shallow or deep) does not appear to have an effect on how efficiently PPN litter burns (Hypothesis 2). Also, a consistent relationship between the moisture content of the fuel and combustion efficiency was not identified (Hypothesis 3). For the low and mid bulk density fuelbeds — there was no difference in the combustion efficiency of the dry and moist fuelbeds. However, the combustion efficiency was different in high bulk density, shallow fuelbeds between the dry and moist groups, thus leading to differing emission factors for CH4. The variability in emission factors for CH4 from the burning of PPN fuelbeds is largely predicted by the combustion efficiency, which itself is driven by fuel bed bulk density.
CONSUME and FOFEM, two of the most commonly used combustion models, use fuel moisture and fuel structure to simulate combustion. Both FOFEM and CONSUME assume that litter fuels, such as ponderosa pine needles, burn almost exclusively via flaming combustion with a high efficiency. This would result in relatively low emissions of CH4, PM2.5, and VOC. Our study finds that the bulk density of litter fuels has a strong influence on the relative amounts of flaming and smoldering and combustion that occurs. This finding indicates that for fuel bed properties typical of many conifer forests, pollutants generated from fires will be higher than that predicted using standard combustion models due to lower than assumed combustion efficiencies.
