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Background: Fire models have used pyrolysis data from oxidising and non-oxidising environments for flaming combustion. In wildland fires pyrolysis, flaming and smouldering combustion typically occur in an oxidising environment (the atmosphere). Aims: Using compositional data analysis methods, determine if the composition of pyrolysis gases measured in non-oxidising and ambient (oxidising) atmospheric conditions were similar. Methods: Permanent gases and tars were measured in a fuel-rich (non-oxidising) environment in a flat flame burner (FFB). Permanent and light hydrocarbon gases were measured for the same fuels heated by a fire flame in ambient atmospheric conditions (oxidising environment). Log-ratio balances of the measured gases common to both environments (CO, CO2, CH4, H2, C6H6O (phenol), and other gases) were examined by principal components analysis (PCA), canonical discriminant analysis (CDA) and permutational multivariate analysis of variance (PERMANOVA). Key results: Mean composition changed between the non-oxidising and ambient atmosphere samples. PCA showed that flat flame burner (FFB) samples were tightly clustered and distinct from the ambient atmosphere samples. CDA found that the difference between environments was defined by the CO-CO2 log-ratio balance. PERMANOVA and pairwise comparisons found FFB samples differed from the ambient atmosphere samples which did not differ from each other. Conclusion: Relative composition of these pyrolysis gases differed between the oxidising and non-oxidising environments. This comparison was one of the first comparisons made between bench-scale and field scale pyrolysis measurements using compositional data analysis. Implications: These results indicate the need for more fundamental research on the early time-dependent pyrolysis of vegetation in the presence of oxygen. Composition of pyrolysis gases measured in non-oxidising and ambient atmospheric conditions has been compared using compositional data analysis. Mean compositions changed between the non-oxidising and ambient atmosphere samples. These results indicate the need for more fundamental research on the early time-dependent pyrolysis of vegetation in the presence of oxygen. [ABSTRACT FROM AUTHOR]

Background: Fire models use pyrolysis data from ground samples and environments that differ from wildland conditions. Two analytical methods successfully measured oxidative pyrolysis gases in wind tunnel and field fires: Fourier transform infrared (FTIR) spectroscopy and gas chromatography with flame-ionisation detector (GC-FID). Compositional data require appropriate statistical analysis. Aims: To determine if oxidative pyrolysis gas composition differed between analytical methods and locations (wind tunnel and field). Methods: Oxidative pyrolysis gas sample composition collected in wind tunnel and prescribed fires was determined by FTIR and GC/FID. Proportionality between gases was tested. Analytical method and location effects on composition were tested using permutational multivariate analysis of variance and the Kruskal–Wallis test. Key results: Gases proportional to each other were identified. The FTIR composition differed between locations. The subcomposition of common gases differed between analytical methods but not between locations. Relative amount of the primary fuel gases (CO, CH4) was not significantly affected by location. Conclusions: Composition of trace gases differed between the analytical methods; however, each method yielded a comparable description of the primary fuel gases. Implications: Both FTIR and GC/FID methods can be used to quantify primary pyrolysis fuel gases for physically-based fire models. Importance of the trace gases in combustion models remains to be determined. Oxidative pyrolysis gases were measured in a wind tunnel and small prescribed burns using two analytical methods. Gas composition measured by FTIR spectroscopy differed between wind tunnel and field fires. The relative amount of the primary fuel gases (CO, CH4) was not significantly affected by fire location. (This paper is part of a Special Issue that includes papers on research presented at the IX International Conference on Forest Fire Research, Coimbra, Portugal, November 2022.) [ABSTRACT FROM AUTHOR]

The methodology of using mobile scanning lidar data for investigation of smoke plume rise and highresolution smoke dispersion is considered. The methodology is based on the lidar-signal transformation proposed recently [Appl. Opt. 48, 2559 (2009)]. In this study, similar methodology is used to create the atmospheric heterogeneity height indicator (HHI), which shows all heights at which the smoke plume heterogeneity was detected by a scanning lidar. The methodology is simple and robust. Subtraction of the initial lidar signal offset from the measured lidar signal is not required. HHI examples derived from lidar scans obtained with the U.S. Forest Service, Fire Sciences Laboratory mobile lidar in areas polluted by wildfires are presented, and the basic details of the methodology are discussed. OCIS codes: 280.3640, 290.1350, 290.2200.

We present an alternative method for determining the total offset in lidar signal created by a daytime background-illumination component and electrical or digital offset. Unlike existing techniques, here the signal square-range-correction procedure is initially performed using the total signal recorded by lidar, without subtraction of the offset component. While performing the square-range correction, the lidar-signal monotonic change due to the molecular component of the atmosphere is simultaneously compensated. After these corrections, the total offset is found by determining the slope of the above transformed signal versus a function that is defined as a ratio of the squared range and two molecular scattering components, the backscatter and transmittance. The slope is determined over a far end of the measurement range where aerosol loading is zero or, at least, minimum. An important aspect of this method is that the presence of a moderate aerosol loading over the far end does not increase dramatically the error in determining the lidar-signal offset. The comparison of the new technique with a conventional technique of the total-offset estimation is made using simulated and experimental data. The one-directional and multiangle measurements are analyzed and specifics in the estimate of the uncertainty limits due to remaining shifts in the inverted lidar signals are discussed. The use of the new technique allows a more accurate estimate of the signal constant offset, and accordingly, yields more accurate lidar-signal inversion results. OCIS codes: 280.3640, 290.1350, 290.2200.

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. OCIS codes: 280.0280, 280.3640.

An experimental method for determining the presence and the level of systematic distortions in lidar data is considered. The method has been developed on the basis of two years of field experiments with the Fire Sciences Laboratory elastic scanning lidar. The influence of multiplicative and additive distortion components is considered using numerical experiments and is illustrated with experimental data. The examination method is most applicable for short wavelengths at which the atmospheric molecular component in clear atmospheres is large enough to stabilize the Kano-Hamilton multiangle solution, based on the assumption of horizontal atmospheric homogeneity. OCIS codes: 280.0280, 280.3640.

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. OCIS codes: 280.3640, 280.0280, 280.1100, 280.1120.

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the National Aeronautics and Space Administration Terra and Aqua spacecrafts have several visible and near-infrared (NIR) channels with resolutions of 250, 500, and 1 km for remote sensing of land surfaces and atmosphere. The MODIS data directly broadcasted to ground receiving stations can have many practical applications, including the rapid assessment of fires and burned areas. In this paper, we describe an empirical technique for remote sensing of burn scars using a single dataset of MODIS NIR channels centered near 1.24 and 2.13 [micro]m. These channels are sensitive to changes in the surface properties induced by the fire and are not obscured by smoke. Therefore, they allow remote sensing of burn scars in the presence of smoke. Detection of burn scars from single MODIS images, without the need of data from previous days, is very useful for near real-time burn scar recognition in operational direct broadcasting systems. The technique is applied to MODIS data acquired over the western U.S. during the summer fire season, the southeastern part of Canada during the summer and spring seasons, and the southeastern part of Australia. The burnt areas estimated from MODIS data are consistent with those estimated from the high spatial resolution Landsat 7 imaging data. Index Terms--Burn scars, fires, Moderate Resolution Imaging Spectroradiometer (MODIS), remote sensing.

The presence of oxygenated organic compounds in condensed smoke of different types of biomass under smoldering, self-sustained smoldering and flaming conditions were analyzed using gas chromatography/mass spectrometry and gas chromatography/flame ionization detection. The results showed that 2-furaldehyde, vinyl acetate, acetol and methanol were the major condensible emissions.