Cyle Wold

Emissions of trace gases and aerosols during the open combustion of biomass in the laboratory

[1] We characterized the gas- and speciated aerosol-phase emissions from the open combustion of 33 different plant species during a series of 255 controlled laboratory burns during the Fire Laboratory at Missoula Experiments (FLAME). The plant species we tested were chosen to improve the existing database for U.S. domestic fuels: laboratory-based emission factors have not previously been reported for many commonly burned species that are frequently consumed by fires near populated regions and protected scenic areas. The plants we tested included the chaparral species chamise, manzanita, and ceanothus, and species common to the southeastern United States (common reed, hickory, kudzu, needlegrass rush, rhododendron, cord grass, sawgrass, titi, and wax myrtle). Fire-integrated emission factors for gas-phase CO2, CO, CH4 ,C 2–4 hydrocarbons, NH3 ,S O2, NO, NO2, HNO3, and particle-phase organic carbon (OC), elemental carbon (EC), SO4� ,N O3 ,C l � ,N a + ,K + , and NH4 generally varied with both fuel type and with the fire-integrated modified combustion efficiency (MCE), a measure of the relative importance of flaming- and smoldering-phase combustion to the total emissions during the burn. Chaparral fuels tended to emit less particulate OC per unit mass of dry fuel than did other fuel types, whereas southeastern species had some of the largest observed emission factors for total fine particulate matter. Our measurements spanned a larger range of MCE than prior studies, and thus help to improve estimates of the variation of emissions with combustion conditions for individual fuels.

Emissions from the laboratory combustion of wildland fuels : Particle morphology and size

[1] The morphology of particles emitted by wildland fires contributes to their physical and chemical properties but is rarely determined. As part of a study at the USFS Fire Sciences Laboratory (FSL) investigating properties of particulate matter emitted by fires, we studied the size, morphology, and microstructure of particles emitted from the combustion of eight different wildland fuels (i.e., sagebrush, poplar wood, ponderosa pine wood, ponderosa pine needles, white pine needles, tundra cores, and two grasses) by scanning electron microscopy. Six of these fuels were dry, while two fuels, namely the tundra cores and one of the grasses, had high fuel moisture content. The particle images were analyzed for their density and textural fractal dimensions, their monomer and agglomerate number size distributions, and three different shape descriptors, namely aspect ratio, root form factor, and roundness. The particles were also probed with energy dispersive X-ray spectroscopy confirming their carbonaceous nature. The density fractal dimension of the agglomerates was determined using two different techniques, one taking into account the three-dimensional nature of the particles, yielding values between 1.67 and 1.83, the other taking into account only the two-dimensional orientation, yielding values between 1.68 and 1.74. The textural fractal dimension that describes the roughness of the boundary of the two-dimensional projection of the particle was between 1.10 and 1.19. The maximum length of agglomerates was proportional to a power a of their diameter and the proportionality constant and the three shape descriptors were parameterized as function of the exponent a.

Chemical Smoke Marker Emissions During Flaming and Smoldering Phases of Laboratory Open Burning of Wildland Fuels

Smoke emitted by prescribed and wild fires can make a substantial contribution to ambient aerosol (McMeeking et al. 2006; Park et al. 2007; Spracklen et al. 2007). Approaches to investigate these contributions have used a variety of different chemical smoke markers, including levoglucosan, produced by thermal degradation of cellulose, and water-soluble potassium (Andreae 1983; Engling et al. 2006; Hays et al. 2002; Simoneit 2002;Ward et al. 2006). Filter sampling is commonly employed to measure smoke markers in ambient and source samples; however, these time-integrated measurements limit knowledge about variability of smoke marker emissions, especially between flaming and smoldering fire phases.

Application of the Kano-Hamilton Multiangle Inversion Method in Clear Atmospheres

An improved measurement methodology and a data-processing technique for multiangle data obtained with an elastic scanning lidar in clear atmospheres are introduced. Azimuthal and slope scans are combined to reduce the atmospheric heterogeneity. Vertical profiles of optical depth and intercept (proportional to the logarithm of the backscatter coefficient) are determined. The purpose of this approach is to identify and remove data points that distort the regression analysis results in order to improve the accuracy of the retrieved optical depth and of the intercept. In addition, the influence of systematic distortions has been investigated. Furthermore, profiles of the optical depth, intercept, and the range-squared-corrected signals have been used to determine the lidar overlap function as a function of range. Simulation and experimental results of this data-processing technique are presented.

Observations of energy transport and rate of spreads from low-intensity fires in longleaf pine habitat – RxCADRE 2012

Wildland fire rate of spread (ROS) and intensity are determined by the mode and magnitude of energy transport from the flames to the unburned fuels. Measurements of radiant and convective heating and cooling from experimental fires are reported here. Sensors were located nominally 0.5 m above ground level. Flame heights varied from 0.3 to 1.8 m and flaming zone depth varied from 0.3 to 3.0 m. Fire ROS derived from observations of fire transit time between sensors was 0.10 to 0.48 m s–1. ROS derived from ocular estimates reached 0.51 m s–1 for heading fire and 0.25 m s–1 for backing fire. Measurements of peak radiant and total energy incident on the sensors during flame presence reached 18.8 and 36.7 kW m–2 respectively. Peak air temperatures reached 1159°C. Calculated fire radiative energy varied from 7 to 162 kJ m–2 and fire total energy varied from 3 to 261 kJ m–2. Measurements of flame emissive power peaked at 95 kW m–2. Average horizontal air flow in the direction of flame spread immediately before, during, and shortly after the flame arrival reached 8.8 m s–1, with reverse drafts of 1.5 m s–1; vertical velocities varied from 9.9 m s–1 upward flow to 4.5 m s–1 downward flow. The observations from these fires contribute to the overall understanding of energy transport in wildland fires.

Modified technique for processing multiangle lidar data measured in clear and moderately polluted atmospheres

We present a modified technique for processing multiangle lidar data that is applicable for relatively clear atmospheres, where the utilization of the conventional Kano–Hamilton method meets significant issues. Our retrieval algorithm allows computing the two-way transmission and the corresponding extinction-coefficient profile in any slope direction searched during scanning. These parameters are obtained from the backscatter term of the Kano–Hamilton solution and the corresponding square-range-corrected signal; the second component of the solution, related with the vertical optical depth, is completely excluded from consideration. The inversion technique was used to process experimental data obtained with the Missoula Fire Sciences Laboratory lidar. Simulated and real experimental data are presented that illustrate the essentials of the data-processing technique and possible variants of the extinction-coefficient profile retrieval.

Determination of the particulate extinction-coefficient profile and the column-integrated lidar ratios using the backscatter-coefficient and optical-depth profiles

A new method is considered that can be used for inverting data obtained from a combined elastic-inelastic lidar or a high spectral resolution lidar operating in a one-directional mode, or an elastic lidar operating in a multiangle mode. The particulate extinction coefficient is retrieved from the simultaneously measured profiles of the particulate backscatter coefficient and the particulate optical depth. The stepwise profile of the column-integrated lidar ratio is found that provides best matching of the initial (inverted) profile of the optical depth to that obtained by the inversion of the backscatter-coefficient profile. The retrieval of the extinction coefficient is made without using numerical differentiation. The method reduces the level of random noise in the retrieved extinction coefficient to the level of noise in the inverted backscatter coefficient. Examples of simulated and experimental data are presented.

Simple algorithm to determine the near-edge smoke boundaries with scanning lidar

We propose a modified algorithm for the gradient method to determine the near-edge smoke plume boundaries using backscatter signals of a scanning lidar. The running derivative of the ratio of the signal standard deviation (STD) to the accumulated sum of the STD is calculated, and the location of the global maximum of this function is found. No empirical criteria are required to determine smoke boundaries; thus the algorithm can be used without a priori selection of threshold values. The modified gradient method is not sensitive to the signal random noise at the far end of the lidar measurement range. Experimental data obtained with the Fire Sciences Laboratory lidar during routine prescribed fires in Montana were used to test the algorithm. Analysis results are presented that demonstrate the robustness of this algorithm.

Validation of smoke plume rise models using ground-based Lidar

Biomass fires can significantly degrade regional air quality through the emission of primary aerosols and the photochemical production of ozone and secondary aerosols. The injection height of smoke from biomass burning into the atmosphere (‘plume rise height’) is one of the critical factors in determining the impact of fire emissions on air quality. Plume rise models are used to simulate plume rise height and prescribe the vertical distribution of fire emissions for input to smoke dispersion and air quality models. While several plume rise models exist, their uncertainties, biases, and application limits when applied to biomass fires are not well characterized. The poor state of model evaluation is due in large part to a lack of appropriate observational datasets. We have initiated a research project to address this critical observation gap. In August of 2013 we performed a multi-agency field experiment designed to obtain the data necessary to improve the air quality models used by agricultural smoke managers in the northwestern United States. In the experiment, the ground-based mobile lidar, developed at the US Forest Service Missoula Fire Science Laboratory, was used to monitor plume rise heights for nine agricultural fires in the northwestern United States. The lidar measurements were compared with plume rise heights calculated with the Briggs equations, which are used in several smoke management tools. Here we present the preliminary evaluation results and provide recommendations regarding the application of the models to agricultural burning based on lidar measurements made in the vicinity of Walla Walla, Washington, on August 24, 2013.

Lidar monitoring of regions of intense backscatter with poorly defined boundaries

The upper height of a region of intense backscatter with a poorly defined boundary between this region and a region of clear air above it is found as the maximal height where aerosol heterogeneity is detectable, that is, where it can be discriminated from noise. The theoretical basis behind the retrieval technique and the corresponding lidar-data-processing procedures are discussed. We also show how such a technique can be applied to one-directional measurements. Examples of typical results obtained with a scanning lidar in smoke-polluted atmospheres and experimental data obtained in an urban atmosphere with a vertically pointing lidar are presented.