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Emissions from a stand replacement prescribed burn were sampled using an unmanned aircraft system (UAS, or “drone”) in Fishlake National Forest, Utah, U.S.A. Sixteen flights over three days in June 2019 provided emission factors for a broad range of compounds including carbon monoxide (CO), carbon dioxide (CO(2)), nitric oxide (NO), nitrogen oxide (NO(2)), particulate matter < 2.5 microns in diameter (PM(2.5)), volatile organic compounds (VOCs) including carbonyls, black carbon, and elemental/organic carbon. To our knowledge, this is the first UAS-based emission sampling for a fire of this magnitude, including both slash pile and crown fires resulting in wildfire-like conditions. The burns consisted of drip torch ignitions as well as ground-mobile and aerial helicopter ignitions of large stands comprising over 1,000 ha, allowing for comparison of same-species emission factors burned under different conditions. The use of a UAS for emission sampling minimizes risk to personnel and equipment, allowing flexibility in sampling location and ensuring capture of representative, fresh smoke constituents. PM(2.5) emission factors varied 5-fold and, like most pollutants, varied inversely with combustion efficiency resulting in lower emission factors from the slash piles than the crown fires.

Methods to accurately estimate spatially explicit fuel consumption are needed because consumption relates directly to fire behavior, effects, and smoke emissions. Our objective was to quantify sparkleberry (Vaccinium arboretum Marshall) shrub fuels before and after six experimental prescribed fires at Fort Jackson in South Carolina. We used a novel approach to characterize shrubs non-destructively from three-dimensional (3D) point cloud data collected with a terrestrial laser scanner. The point cloud data were reduced to 0.001 m–3 voxels that were either occupied to indicate fuel presence or empty to indicate fuel absence. The density of occupied voxels was related significantly by a logarithmic function to 3D fuel bulk density samples that were destructively harvested (adjusted R2 = .32, P < .0001). Based on our findings, a survey-grade Global Navigation Satellite System may be necessary to accurately associate 3D point cloud data to 3D fuel bulk density measurements destructively collected in small (submeter) shrub plots. A recommendation for future research is to accurately geolocate and quantify the occupied volume of entire shrubs as 3D objects that can be used to train models to map shrub fuel bulk density from point cloud data binned to occupied 3D voxels.

In this study we capture and identify pyrolysis gases from prescribed burns conducted in pine forests with a shrub understory using a manual extraction device. The device selectively sampled emissions ahead of the flame front, minimizing collection of oxidized gases, with the captured gases analyzed in the laboratory using infrared absorption spectroscopy. Results show that emission ratios (ER) relative to CO for ethene, and acetylene were significantly greater than previous fire studies, suggesting that the sample device was able to collect gases prior to ignition. Further evidence that ignition had not begun was corroborated by novel infrared detections of several species, in particular naphthalene. With regards to oxygenated species, several aldehydes (acrolein, furaldehyde, acetaldehyde, formaldehyde) and the carboxylic acids (formic, acetic) were all observed; results show that ERs for acetaldehyde were noticeably greater while ERs for formaldehyde and acetic acid were lower compared to other studies. The acetylene-to-furan ratio also suggests that high temperature pyrolysis was the dominant process generating the collected gases. This hypothesis is further supported by the presence of HCN and the absence of NH3.

Reactive nitrogen (Nr) within smoke plumes plays important roles in the production of ozone, the formation of secondary aerosols, and deposition of fixed N to ecosystems. The Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN) field campaign sampled smoke from 23 wildfires throughout the western U.S. during summer 2018 using the NSF/NCAR C-130 research aircraft. We empirically estimate Nr normalized excess mixing ratios and emission factors from fires sampled within 80 min of estimated emission and explore variability in the dominant forms of Nr between these fires. We find that reduced N compounds comprise a majority (39%-80%; median = 66%) of total measured reactive nitrogen (ΣNr) emissions. The smoke plumes sampled during WE-CAN feature rapid chemical transformations after emission. As a result, within minutes after emission total measured oxidized nitrogen (ΣNOy) and measured total ΣNHx (NH3 + pNH4) are more robustly correlated with modified combustion efficiency (MCE) than NOx and NH3 by themselves. The ratio of ΣNHx/ΣNOy displays a negative relationship with MCE, consistent with previous studies. A positive relationship with total measured ΣNr suggests that both burn conditions and fuel N content/volatilization differences contribute to the observed variability in the distribution of reduced and oxidized Nr. Additionally, we compare our in situ field estimates of Nr EFs to previous lab and field studies. For similar fuel types, we find ΣNHx EFs are of the same magnitude or larger than lab-based NH3 EF estimates, and ΣNOy EFs are smaller than lab NOx EFs.

The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.

Reliable estimates of pre-burn biomass and fuel consumption are important to estimate wildland fire emissions and assist in prescribed burn planning. We present empirical models for predicting fuel consumption in natural fuels from 60 prescribed fires in ponderosa pine-dominated forests in the western US and 60 prescribed fires in long-needle pine forests in the southeastern US. There was high variability across sites, but total surface fuel biomass was generally much lower on southern sites (23.0 ± 11.6 Mg ha −1 ) than western sites (61.5 ± 35.8 Mg ha −1 ). Differences in surface fuel composition, pre-burn loading and fuel consumption between the southern and western pine consumption datasets justify the development of regional models for predicting fuel consumption. Southern pine models of herb, shrub and 1-h consumption have close model fit with narrow prediction intervals across the range of sampled values. Relationships between 10-h and 100-h pre-burn loading and consumption produced models with reasonable fit but with no significant correlation with fuel moisture. Model fit of litter and duff consumption models was relatively poor compared to the other southern fuel categories. Western models were developed for 1-h, 10-h and 100-h fine wood, sound coarse wood, rotten coarse wood, litter and duff. All western models had high coefficients of variability, and model residuals indicate higher uncertainty with increasing pre-burn biomass. Although empirical models are widely used, they have limitations in that they are constrained by burning conditions and ranges of predictor variables.

There is limited research on the exposure of wildland firefighters to smoke because of the operational obstacles when monitoring air pollutants in the field. In this work, a grid of portable sensors was used to measure PM2.5 and CO concentrations in the near-source region during the burn of two shrubland research blocks in Central Portugal. Strong spatial variability of smoke levels was observed in the analysis of the ratios between mean concentrations of neighbouring sensors, with values as high as 4.4 for PM2.5 and 7.4 for CO. These large gradients were registered at a distance of only 5 m suggesting that considerable differences on individual exposure can occur depending on the location of that individual in relation to the smoke plume trajectory. Also, peak events of 2–3 times the mean were observed in periods exceeding 6 min. In the two experiments, the average concentrations of both PM2.5 and CO were higher during smouldering, which represents a risk of acute exposure due to the closer proximity of firefighters to the emission source during mop-up, stressing the importance of wearing portable gas detectors for managing critical exposure. The collected data constitutes a step forward in the effort to understand the mechanisms controlling the exposure during firefighting operations, by providing a source of information on near-ground concentration fluctuations within a biomass-burning smoke plume at a fine spatial-temporal resolution.

The FireFlux II experiment was conducted in a tall grass prairie located in south-east Texas on 30 January 2013 under a regional burn ban and high fire danger conditions. The goal of the experiment was to better understand micrometeorological aspects of fire spread. The experimental design was guided by the use of a coupled fire–atmosphere model that predicted the fire spread in advance. Preliminary results show that after ignition, a surface pressure perturbation formed and strengthened as the fire front and plume developed, causing an increase in wind velocity at the fire front. The fire-induced winds advected hot combustion gases forward and downwind of the fire front that resulted in acceleration of air through the flame front. Overall, the experiment collected a large set of micrometeorological, air chemistry and fire behaviour data that may provide a comprehensive dataset for evaluating and testing coupled fire–atmosphere model systems.

As carbon modeling tools become more comprehensive, spatial data are needed to improve quantitative maps of carbon emissions from fire. The Wildland Fire Emissions Information System (WFEIS) provides mapped estimates of carbon emissions from historical forest fires in the United States through a web browser. WFEIS improves access to data and provides a consistent approach to estimating emissions at landscape, regional, and continental scales. The system taps into data and tools developed by the U.S. Forest Service to describe fuels, fuel loadings, and fuel consumption and merges information from the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration on fire location and timing. Currently, WFEIS provides web access to Moderate Resolution Imaging Spectroradiometer (MODIS) burned area for North America and U.S. fire-perimeter maps from the Monitoring Trends in Burn Severity products from the USGS, overlays them on 1-km fuel maps for the United States, and calculates fuel consumption and emissions with an open-source version of the Consume model. Mapped fuel moisture is derived from daily meteorological data from remote automated weather stations. In addition to tabular output results, WFEIS produces multiple vector and raster formats. This paper provides an overview of the WFEIS system, including the web-based system functionality and datasets used for emissions estimates. WFEIS operates on the web and is built using open-source software components that work with open international standards such as keyhole markup language (KML). Examples of emissions outputs from WFEIS are presented showing that the system provides results that vary widely across the many ecosystems of North America and are consistent with previous emissions modeling estimates and products.

Reliable predictions of fuel consumption are critical in the eastern United States (US), where prescribed burning is frequently applied to forests and air quality is of increasing concern. CONSUME and the First Order Fire Effects Model (FOFEM), predictive models developed to estimate fuel consumption and emissions from wildland fires, have not been systematically evaluated for application in the eastern US using the same validation data set. In this study, we compiled a fuel consumption data set from 54 operational prescribed fires (43 pine and 11 mixed hardwood sites) to assess each model’s uncertainties and application limits. Regions of indifference between measured and predicted values by fuel category and forest type represent the potential error that modelers could incur in estimating fuel consumption by category. Overall, FOFEM predictions have narrower regions of indifference than CONSUME and suggest better correspondence between measured and predicted consumption. However, both models offer reliable predictions of live fuel (shrubs and herbaceous vegetation) and 1 h fine fuels. Results suggest that CONSUME and FOFEM can be improved in their predictive capability for woody fuel, litter, and duff consumption for eastern US forests. Because of their high biomass and potential smoke management problems, refining estimates of litter and duff consumption is of particular importance.

Fuel consumption specifies the amount of vegetative biomass consumed during wildland fire. It is a two-stage process of pyrolysis and combustion that occurs simultaneously and at different rates depending on the characteristics and condition of the fuel, weather, topography, and in the case of prescribed fire, ignition rate and pattern. Fuel consumption is the basic process that leads to heat absorbing emissions called greenhouse gas and other aerosol emissions that can impact atmospheric and ecosystem processes, carbon stocks, and land surface reflectance. It is a critical requirement for greenhouse gas emission inventories. There are several fuel consumption models widely used by scientists and land managers including the First Order Fire Effects Model, Consume, and CanFIRE. However, these models have not been thoroughly evaluated with an independent, quality assured, fuel consumption data set. Furthermore, anecdotal evidence indicates the models have limited ability to predict consumption of specific fuel bed categories such as tree crowns, deep organic layers, and rotten logs that can contribute significantly to greenhouse gases. If we are to move forward in our ability to assess the contribution of wildland fire to greenhouse gas to the atmosphere, our current fuel consumption models must be evaluated and modified to improve their predictive capabilities. Finally, information is lacking on how much black and brown carbon from wildland fire is generated during the combustion process and how much remains on site becoming sequestered in soils, partially offsetting greenhouse gas emissions. This synthesis focuses on the process and modeling of fuel consumption and knowledge gaps that will improve our ability to predict fuel consumption and the resulting greenhouse gas emissions.

Mastication is an increasingly common fuels treatment that redistributes ‘‘ladder’’ fuels to the forest floor to reduce vertical fuel continuity, crown fire potential, and fireline intensity, but fuel models do not exist for predicting fire behavior in these fuel types. Recent fires burning in masticated fuels have behaved in unexpected and contradictory ways, likely because the shredded, compact fuel created when trees and shrubs are masticated contains irregularly shaped pieces in mixtures quite different from other woody fuels. We review fuels characteristics and fire behavior in masticated fuels across the United States. With insights from the few laboratory and field burning experiments conducted, we highlight the variation likely to occur across different ecosystems in which these treatments are being widely implemented. Masticated debris has a propensity to flame and smolder for long durations. Fuel variability and vegetation response will likely influence whether or not treatments reduce long-term fire hazard. We identify key science needs that will better elucidate fire behavior and effects in these treatments. With mastication widely applied in an expanding wildland–urban interface it is crucial to understand how such fuels burn. What we learn about combustion in these fuels will inform effective fuels management in these and other mixed fuels.

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

Fuel Loading Models (FLMs) and Fuel Characteristic Classification System (FCCSs) fuelbeds are used throughout wildland fire science and management to simplify fuel inputs into fire behavior and effects models, but they have yet to be thoroughly evaluated with field data. In this study, we used a large dataset of Forest Inventory and Analysis (FIA) surface fuel estimates (n = 13,138) to create a new fuel classification called Fuel Type Groups (FTGs) from FIA forest type groups, and then keyed an FLM, FCCS, and FTG class to each FIA plot based on fuel loadings and stand conditions. We then compared FIA sampled loadings to the keyed class loading values for four surface fuel components (duff, litter, fine woody debris, coarse woody debris) and to mapped FLM, FCCS, and FTG class loading values from spatial fuel products. We found poor performances (R2 < 0.30) for most fuel component loadings in all three classifications that, in turn, contributed to poor mapping accuracies. The main reason for the poor performances is the high variability of the four fuel component loadings within classification categories and the inherent scale of this variability does not seem to match the FIA measurement scale or LANDFIRE mapping scale.

[1] Biomass burning is a significant contributor to atmospheric carbon emissions but may also provide an avenue in which fire-affected ecosystems can accumulate carbon over time, through the generation of highly resistant fire-altered carbon. Identifying how fuel moisture, and subsequent changes in the fire behavior, relates to the production of fire-altered carbon is important in determining how persistent charred residues are following a fire within specific fuel types. Additionally, understanding how mastication (mechanical forest thinning) and fire convert biomass to black carbon is essential for understanding how this management technique, employed in many fire-prone forest types, may influence stand-level black carbon in soils. In this experimental study, 15 masticated fuel beds, conditioned to three fuel moisture ranges, were burned, and production rates of pyrogenic carbon and soot-based black carbon were evaluated. Pyrogenic carbon was determined through elemental analysis of the post-fire residues, and soot-based black carbon was quantified with thermochemical methods. Pyrogenic carbon production rates ranged from 7.23% to 8.67% relative to pre-fire organic carbon content. Black carbon production rates averaged 0.02% in the 4–8% fuel moisture group and 0.05% in the 13–18% moisture group. A comparison of the ratio of black carbon to pyrogenic carbon indicates that burning with fuels ranging from 13% to 15% moisture content resulted in a higher proportion of black carbon produced, suggesting that the precursors to black carbon were indiscriminately consumed at lower fuel moistures. This research highlights the importance of fuel moisture and its role in dictating both the quantity and quality of the carbon produced in masticated fuel beds.

Mechanical (e.g., shearblading) and manual (e.g., thinning) fuel treatments have become the preferred strategy of many fire managers and agencies for reducing fire hazard in boreal forests. This study attempts to characterize the effectiveness of four fuel treatments through direct measurement of fire intensity and forest floor consumption during a single prescribed burn. The treatments included (1) thinning trees and removing debris (THIN-REMOVE-1 and -2), (2) thinning trees and burning the debris onsite, (3) shearblading and leaving the debris in place (SHEAR), and (4) shearblading and piling the debris in windrows (SHEAR-ROW). Fire burned through treatments 1, 3, and 4 and one control unit. The highest fire intensities (maximum temperature of 1150 °C, maximum heat flux of 227 kW·m–2, and fire cumulative energy release of 4277 J·m–2) were measured in the control. Treatment 1 exhibited a peak temperature of 267 °C, peak heating of 16 kW·m–2, and cumulative energy release of 2600 J·m–2. Treatments 3 and 4 exhibited peak temperatures of 170 and 66 °C, peak heating of 51 and 3 kW·m–2, and cumulative energy release of 2500 and 1800 J·m–2, respectively. The thinned treatment showed the most significant impact in the context of reduced heat release.

Background/objective A study was undertaken at the United States Department of Energy's Savannah River Site (SRS), Aiken, South Carolina to investigate radionuclide activity concentrations in litter and duff from select areas at SRS. Litter (i.e. vegetative debris) and duff (i.e. highly decomposed vegetative debris) can often be the major fuels consumed during prescribed burns and have potential to release radiological contaminants into the environment. Methods Repeated samples from 97 locations were collected systematically across SRS and analyzed for radionuclide activity. Radionuclide activity concentrations found in litter and duff were compared. As spatial trends were of interest, spatial distributions of radionuclide activity concentrations found in litter and duff and spatial dependency amongst the data were explored. Results 7 Be, 40 K, and 137 Cs showed statistically significant proportional differences between litter and duff samples. Duff sample concentrations for 137 Cs ( p 40 K ( p = 0.0015) were statistically higher compared to litter samples. 7 Be activity concentrations were statistically higher in litter as compared to duff ( p 40 K litter and duff samples, spatial correlation tests were not significant at p = 0.05 and the maps did not indicate any apparent high concentrations centered near possible radionuclide sources (i.e. SRS facilities). For 7 Be litter samples, significant spatial correlation was calculated ( p = 0.0085). No spatial correlation was evident in the 7 Be duff samples ( p = 1.0000) probably due to small sample size ( n = 7). 137 Cs litter and duff samples showed significant spatial correlations ( p p Conclusions To date, few studies characterize radionuclide activity concentrations in litter and duff, and to our knowledge none present spatial analysis. Key findings show that across SRS, 137 Cs is the primary radionuclide of concern, with the highest number of samples reported above MDC in litter (51.4%) and duff samples (83.2%). However, 137 Cs litter and duff spatial trends in the maps generated from the kriging parameters do not appear to directly link the areas with higher activity concentrations with SRS facilities. The results found herein provide valuable baseline monitoring data for future studies of forest surface fuels and can be used to evaluate changes in radioactivity in surface fuels in the southeast region of the U.S.

Fuel treatment effectiveness in Southern forests has been demonstrated using fire behavior modeling and observations of reduced wildfire area and tree damage. However, assessments of treatment effectiveness may be improved with a more rigorous accounting of the fuel characteristics. We present two case studies to introduce a relatively new approach to characterizing fuels and predicting potential fire behavior, fuel consumption, and emissions in Southern forests using the Fuel Characteristic Classification System (FCCS) and Consume. The first case study provides fine-scale ( Results from the fine-scale assessment indicate that fuel treatments reduce reaction intensity, rate of spread, and flamelength by up to 58%, 57%, and 63%, respectively. Fuel loading of strata that control surface fire behavior (i.e., shrubs, grasses, fine woody fuels, and litter) range from 32.0 Mg ha−1 in the thinned, untreated unit to 8.5 Mg ha−1 in the unthinned unit treated with herbicides and prescribed fire. Based on model predictions, up to 80% less fuel would be consumed with concomitant reduction in emissions during a wildfire occurring in the treated units compared to the untreated unit. Assessments of potential fire behavior across the study area indicate that overall hazard is low to moderate for this forested landscape. However, localized areas of high surface fire and crown fire potential were identified. Plot- and stand-based modeling both suggest that the potential for high to extreme fire behavior exists for this landscape. Combined, the two case studies highlight the ability of the FCCS to represent measured fuel characteristics and predict differences in potential fire behavior resulting from fuel treatments. Even small differences in fuel characteristics resulting from fuel treatments or site variation could be detected, allowing the effects of both ecological processes and management actions to be quantified.

Fire hazard mitigation planning requires an accurate accounting of fuel complexes to predict potential fire behavior and effects of treatment alternatives. In the southeastern United States, rapid vegetation growth coupled with complex land use history and forest management options requires a dynamic approach to fuel characterization. In this study we assessed potential surface fire behavior with the Fuel Characteristic Classification System (FCCS), a tool which uses inventoried fuelbed inputs to predict fire behavior. Using inventory data from 629 plots established in the upper Atlantic Coastal Plain, South Carolina, we constructed FCCS fuelbeds representing median fuel characteristics by major forest type and age class. With a dry fuel moisture scenario and 6.4 km h −1 midflame wind speed, the FCCS predicted moderate to high potential fire hazard for the majority of the fuelbeds under study. To explore fire hazard under potential future fuel conditions, we developed fuelbeds representing the range of quantitative inventory data for fuelbed components that drive surface fire behavior algorithms and adjusted shrub species composition to represent 30% and 60% relative cover of highly flammable shrub species. Results indicate that the primary drivers of surface fire behavior vary by forest type, age and surface fire behavior rating. Litter tends to be a primary or secondary driver in most forest types. In comparison to other surface fire contributors, reducing shrub loading results in reduced flame lengths most consistently across forest types. FCCS fuelbeds and the results from this project can be used for fire hazard mitigation planning throughout the southern Atlantic Coastal Plain where similar forest types occur. The approach of building simulated fuelbeds across the range of available surface fuel data produces sets of incrementally different fuel characteristics that can be applied to any dynamic forest types in which surface fuel conditions change rapidly.

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation System. The fundamental fire intensity algorithms in these systems require surface fire behavior fuel models and canopy cover to model surface fire behavior. Canopy base height, stand height, and canopy bulk density are required in addition to surface fire behavior fuel models and canopy cover to model crown fire activity. Several surface fuel and canopy classification efforts have used various remote sensing and ecological relationships as core methods to develop the spatial layers. All of these methods depend upon consistent and temporally constant interpretations of crown attributes and their ecological conditions to estimate surface fuel conditions. This study evaluates modeled fire behavior for an 80,000 ha tract of land in the Atlantic Coastal Plain of the southeastern US using three different data sources. The Fuel Characteristic Classification System (FCCS) was used to build fuelbeds from intensive field sampling of 629 plots. Custom fire behavior fuel models were derived from these fuelbeds. LANDFIRE developedmore » surface fire behavior fuel models and canopy attributes for the US using satellite imagery informed by field data. The Southern Wildfire Risk Assessment (SWRA) developed surface fire behavior fuel models and canopy cover for the southeastern US using satellite imagery. Differences in modeled fire behavior, data development, and data utility are summarized to assist in determining which data source may be most applicable for various land management activities and required analyses. Characterizing fire behavior under different fuel relationships provides insights for natural ecological processes, management strategies for fire mitigation, and positive and negative features of different modeling systems. A comparison of flame length, rate of spread, crown fire activity, and burn probabilities modeled with FlamMap shows some similar patterns across the landscape from all three data sources, but there are potentially important differences. All data sources showed an expected range of fire behavior. Average flame lengths ranged between 1 and 1.4 m. Rate of spread varied the greatest with a range of 2.4-5.7 m min{sup -1}. Passive crown fire was predicted for 5% of the study area using FCCS and LANDFIRE while passive crown fire was not predicted using SWRA data. No active crown fire was predicted regardless of the data source. Burn probability patterns across the landscape were similar but probability was highest using SWRA and lowest using FCCS.« less

Climate change has increased the area affected by forest fires in boreal North America. An analysis of the depth of burning in forests and peatlands in Alaska indicates that ground-layer combustion has accelerated regional carbon losses.

In many fire-prone forests in the United States, changes occurring in the last century have resulted in overstory structures, conifer densities, down woody structure and fuel loads that deviate from those described historically. With these changes, forests are presumed to be unsustainable. Broad-scale treatments are proposed to reduce fuels and promote stand development on trajectories toward more sustainable structures. Yet little research to date has identified the effects of these treatments, especially in low elevation dry ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) forests. We report initial fuelbed conditions and changes immediately and 4–6 years after fuel reduction treatments in an operational-scale, replicated (N = 4), completely randomized experiment in northeastern Oregon. Treatments included a single entry thin from below conducted in 1998, a late season burn conducted in 2000, a thin followed by burning (thin + burn), and a no action treatment which served as a control. Between 1998 and 2004, litter mass declined about 4.4 Mg ha−1 in thin units, about 4.1 Mg ha−1 in thin + burn units, and about 1.5 Mg ha−1 in burn units. Duff mass did not change with treatment. Mass of woody fuels in the 1 and 10 h timelag classes increased in thin units immediately after treatment, but fell to nearly pre-treatment levels by 2004. Mass of woody fuels in the 100 h timelag class increased about 1.6 Mg ha−1 in thin units, and decreased about 0.7 Mg ha−1 in burn units and about 0.1 Mg ha−1 in thin + burn units. There was no difference in the change in total woody fuel mass among all treatments. About 62% of the residual trees in the burn and the thin + burn units were charred; charring extended up the bole about 1.1 m. About 50% of the residual trees in the burn and thin + burn units had scorched lower crowns. Mean scorch height was 4.3 m. Log density was greater in control units compared to actively treated units and greater in the thin units compared to burn or thin + burn units. We used the Fuel Characteristic Classification System (FCCS) to construct a representative fuelbed for each unit from inventoried data and to calculate three indices of fire potential as measures of the change in fire hazard resulting from our treatments: surface fire behavior, crown fire behavior, and fuels available for consumption. Projected flame length, rate of spread, and reaction intensity are derived as metrics of future surface fire behavior. These results are discussed in the context of management options for restoration of ecosystem health in similar low elevation dry ponderosa pine and Douglas-fir forests.

Communicating emissions impacts to the public can sometimes be difficult because quantitatively conveying smoke concentrations is complicated. Regulators and land managers often refer to particulate-matter concentrations in micrograms per cubic meter, but this may not be intuitive or meaningful to everyone. The primary purpose of this guide is to serve as a tool for communicating potential particulate matter (PM2.5) levels during wildfire events using visual representation. Examples of visibility impairment under various levels of smoke concentration and humidity have been modeled using the WinHaze program.

Wildland fuel characteristics are used in many applications of operational fire predictions and to understand fire effects and behaviour. Even so, there is a shortage of information on basic fuel properties and the physical characteristics of wildland fuels. The Fuel Characteristic Classification System (FCCS) builds and catalogues fuelbed descriptions based on realistic physical properties derived from direct or indirect observation, inventories, expert knowledge, inference, or simulated fuel characteristics. The FCCS summarizes and calculates wildland fuel characteristics, including fuel depth, loading, and surface area. Users may modify fuelbeds and thereby capture changing fuel conditions over time and (or) under different management prescriptions. Fuel loadings from four sample fuelbed pairs (i.e., pre- and post-prescribed fire) were calculated and compared by using FCCS to demonstrate the versatility of the system and how individual fuel components, such as shrubs, nonwoody fuels, woody fuels, and litter, can be calculated and summarized. The ability of FCCS to catalogue and summarize complex fuelbeds and reflect dynamic fuel conditions allows calculated results to be used in a variety of applications including surface and crown fire predictions, carbon assessments, and wildlife habitat management.

Wildland fuelbed characteristics are temporally and spatially complex and can vary widely across regions. To capture this variability, we designed the Fuel Characteristic Classification System (FCCS), a national system to create fuelbeds and classify those fuelbeds for their capacity to support fire and consume fuels. This paper describes the structure of the fuelbeds internal to FCCS. Fuelbeds are considered relatively homogeneous units on the landscape, representing distinct combustion environments that determine potential fire behaviour and effects. The FCCS fuelbeds are organized into six strata: canopy, shrubs, nonwoody fuels, woody fuels, litter–lichen–moss, and ground fuels. Fuelbeds are described by several qualitative and quantitative physical and biological variables with emphasis on characteristics useful for fuels management and fire behaviour planning. The FCCS includes 216 fuelbeds that represent the major vegetation types of the United States. The FCCS fuelbeds can be used as presented or modified to create customized fuelbeds with general or site-specific data to address fire science management or research questions. This system allows resource managers to evaluate wildland fuels operations and management activities, fire hazard, and ecological and air quality impacts at small and large spatial scales. The FCCS fuelbeds represent the United States, although the system has the potential for building fuelbeds for international application.

In forests historically maintained by frequent fire, reintroducing fire after decades of exclusion often causes widespread overstory mortality. To better understand this phenomenon, we subjected 16 fire-excluded (ca. 40 years since fire) 10 ha longleaf pine ( Pinus palustris Mill.) stands to one of four replicated burning treatments based on volumetric duff moisture content (VDMC): wet (115% VDMC); moist (85% VDMC); dry (55% VDMC); and a no-burn control. During the first 2 years postfire, overstory pines in the dry burns suffered the greatest mortality (mean 20.5%); pine mortality in the wet and moist treatments did not differ from the control treatment. Duff reduction was greatest in the dry burns (mean 46.5%), with minimal reduction in the moist and wet burns (14.5% and 5%, respectively). Nested logistic regression using trees from all treatments revealed that the best predictors of individual pine mortality were duff consumption and crown scorch (P < 0.001; R2 = 0.34). Crown scorch was significant only in dry burns, whereas duff consumption was significant across all treatments. Duff consumption was related to moisture content in lower duff (Oa; R2 = 0.78, P < 0.001). Restoring fire to long-unburned forests will require development of burn prescriptions that include the effects of duff consumption, an often overlooked fire effect.

Fuel reduction by mechanical thinning and removal was studied in mixed-conifer stands in northeastern Oregon between 1995 and 1997. A single-grip harvester was coupled with either a forwarder or a skyline yarding system, and operational economics, fuel reduction, stand damage, soil disturbance, effects on soil biota and down-woody material were measured in three replicates of paired stands. After logging with the harvester, the two log-extraction systems achieved nearly equivalent fuel reduction with 45.7 and 46.8% mass reduction by the forwarder and skyline system, respectively. Fine-woody fuel increased slightly in all units, but mass of heavy fuels decreased. Most mass reduction in the forest floor occurred in the duff layer with 56 and 49% reduction in forwarder and skyline units, respectively. Reduction in stem density and basal area were similar for the two extraction systems; in forwarder units stem density was reduced by 61.6% and basal area by 55.4%, while in skyline units stem density was reduced by 66.5% and basal area by 51.1%. Of seedlings and trees examined, 32% had noticeable damage after harvest. Damage included bole wounding (38.9% of damaged stems), bark scraping (35.0%), wrenched stems (28.9%), broken branches (26.5%), broken terminal leaders (15.4%), and crushed foliage (4.1%). More damage occurred to residual large trees than to seedlings. Both log-extraction systems met the silvicultural prescription of reducing fuel and protecting residual large-diameter western larch, Engelmann spruce, Douglas-fir, and lodgepole pine. While fuel, stem, and basal area reduction lowered fire risk from a model 10 to a model 8 in all stands, large-woody material for wildlife also changed. Mean log length was lower in harvested units relative to unharvested controls, but this did not decrease occupation of logs by ants or the activities of woodpeckers feeding on them. Of 37 logged hectares, 1.4% (0.5 ha) of the soil area was compacted, mostly in forwarder units, within landings, and within trails close to landings. The percent area with displaced soil varied from 5 to 43% among units and was located within trails or in intertrail areas between the trails. Light displacement of soil resulted in a short-term increase in the abundance of soil microarthropods. The effects of compaction on litter microarthropods was more persistent, with lower numbers in compacted litter a year after harvest. While revenue was similar for forwarder and skyline units ($68 vs. $70/metric ton, respectively), total operational costs were $81/metric ton in the skyline units, compared to $46/metric ton in the forwarder units. These results are discussed in the context of options available to managers for balancing fuel reduction needs with both environmental and economic constraints. West. J. Appl. For. 18(4):238–249.

The inherent spatial and temporal heterogeneity of fuelbeds in forests of the southeastern United States may require fine scale fuel measurements for providing reliable fire hazard and fuel treatment effectiveness estimates. In a series of five papers, an intensive, fine scale fuel inventory from the Savanna River Site in the southeastern United States is used for building fuelbeds and mapping fire behavior potential, evaluating fuel treatment options for effectiveness, and providing a comparative analysis of landscape modeled fire behavior using three different data sources including the Fuel Characteristic Classification System, LANDFIRE, and the Southern Wildfire Risk Assessment. The research demonstrates that fine scale fuel measurements associated with fuel inventories repeated over time can be used to assess broad scale wildland fire potential and hazard mitigation treatment effectiveness in the southeastern USA and similar fire prone regions. Additional investigations will be needed to modify and improve these processes and capture the true potential of these fine scale data sets for fire and fuel management planning.

Agricultural and silvicultural biomass burning is practiced in many undeveloped portions of the Amazon basin. In Rond nia, Brazil, such burning is restricted to a brief period in the dry season of August and September to minimize the duration of air quality impacts and to attempt to control escaped fires. During this period, much of the region and the communities within it experience significant exposure to smoke from agricultural and forest fires. In cooperation with Brazilian scientists of the University of Brasilia, the Brazilian Organization for Agricultural Research (EMBRAPA), and the Alternative to Slash and Burn Program coordinated by the International Center for Research in Agroforestry (ICRAF), ambient air quality was measured in Theobroma, a small town in Rond nia, during one week of the open burning period of 1995 to supplement available air quality data and to foster public awareness of the impacts of widespread fires. Personal sampling equipment was used to measure ambient levels of formaldehyde (HCHO), acrolein, CO, benzene, and respirable PM in outdoor air. The data obtained were compared with established Brazilian and U.S. ambient air quality guidelines. Ambient levels of respirable PM averaged 191 microg/m3, HCHO averaged 12.8 ppb, CO averaged 4.2 ppm, and benzene averaged 3.2 ppb. Almost all acrolein samples were less than the detection limit of 1 ppb. The results showed that the public can be exposed to relatively high levels of pollutants under the prescribed burning smoke management strategy of a two- to three-week prescription burning period, although this is an improvement over past years when burning was unregulated and continued through most of the dry season. The results also demonstrate the feasibility of using personal exposure monitoring equipment for low-cost surveys of ambient air quality in polluted regions.

Timber harvesting residues have typically been burned within coniferous forest areas of the eastern Cascade Mountains of Washington State. Concerns about air pollution and quantities of coarse woody debris have generated interest in alternative residue treatments that will clear areas for planting and still reduce fire hazard. A total of six residue treatments were compared (three slash treatments where residues were burned (spring broadcast burning, fall broadcast burning, piling and burning) and three treatments where residues were not burned (clearing, chopping, pulling unmerchantable material)), along with no slash treatment to determine the effects of alternative approaches on soils and seedlings. Slash-treatment effects on soil bulk density and temperature, air temperature, and seedling growth and survival were examined at four different sites in the eastern Cascade Mountains. Results show that seedling performance was best with spring broadcast burning across all sites over five years of growth. Average height growth of Douglas-fir (Pseudotsuga menziesii) and lodgepole pine (Pinus contorta) over five years was 90 cm in the spring broadcast burn, with 75, 72, 71, 71, 66, and 61 cm for no slash treatment, piling and burning, pulling unmerchantable material, chopping, fall broadcast burn, and clearing, respectively. Seedling height growth may be related to soil temperatures that are closer to optimal for root and shoot growth when large quantities of slash were not insulating the soil. Soil bulk density did not appear to affect seedling growth (bulk density ranged from 0.7 to 1.15 g cm−3). None of the slash treatments that avoid burning increased growth relative to no slash treatment, and some may adversely affect survival. If slash burning can not be used to reduce quantities of timber harvesting residues, then leaving slash untreated appears to be the best alternative for seedling growth.

Summary This paper describes the procedures and data used to develop a database of 28 fire, fuels, and smoke attributes for the broad-scale scientific assessment of the Interior Columbia River Basin. These attributes relate to three general areas: (1) fire weather, fuel moisture, and fire characteristics; (2) fuel loading and fuel consumption; and (3) PM10 smoke emissions. The process flow and development protocols for creation of the database are fully described and illustrated, with examples provided where appropriate. This database was developed for application to a certain geographic area with parameters specific to both the biophysical environment and the management issues of that area. However, the methods and protocols used to develop this comprehensive suite of fire-related data are applicable to any ecosystem for which predictions are needed for wildfire hazard, fire potential, biomass consumption, and smoke emissions.

Prescribed burning of slash following tree harvest is a standard practice to reduce fire hazard and prepare seed beds for planting conifers. This study examined the co-occurrence and intensity of hydrophobic and allelopathic layers created in sand pits under burned slash piles and broadcast slash. Following slash burning, 24 sand cores were taken from the sand pits and analyzed for water repellency and allelopathic effects on germination, emergence, and height growth of a bioassay species, blue wildrye (Elymus glaucus Buckley). Water drop penetration that was instantaneous in untreated sand cores was delayed in sand cores from burn treatments for 5 to 90 s in seven cores and for >270 s in five cores. Seedling emergence and height of the bioassay species declined in both the created hydrophobic sand layer and in an allelopathic zone of wettable sand immediately below the hydrophobic layer. Lack of allelopathic response when free water was present suggests that allelopathic effects are exhibited only under unsaturated soil conditions. Results indicate that nonwettable soils and allelopathy effects will act in unison to reduce water penetration and slow plant establishment following wildfires or prescribed burns.

This work addresses the exposure of firefighters to carbon monoxide (CO) contained in smoke. We have measured the time and space variation of firefighters’ exposure to CO concentration levels during a real scale fire experiment. A model for the estimation of personal exposure of firefighters to smoke was developed. Based on the combination of georeferenced location of a firefighter and on computed air quality levels the model calculates the individual exposure for a given period. Good agreement was found between estimated and measured averaged exposure during the fire experiments. The information on the individual exposure of firefighters can support the management of the crew positioning by anticipating potentially critical exposure levels and recommending safer routes for the attack.

Smoke from forest fires contains significant amounts of gaseous and particulate pollutants. Firefighters exposed to wildland fire smoke can suffer from several acute and chronic adverse health effects. Consequently, exposure data are of vital importance for the establishment of cause/effect relationships between exposure to smoke and firefighter health effects. The aims of this study were to (1) characterize the relationship between wildland smoke exposure and medical parameters and (2) identify health effects pertinent to wildland forest fire smoke exposure. In this study, firefighter exposure levels of carbon monoxide (CO), nitrogen dioxide (NO₂), and volatile organic compounds (VOC) were measured in wildfires during three fire seasons in Portugal. Personal monitoring devices were used to measure exposure. Firefighters were also tested for exhaled nitric oxide (eNO) and CO before and after their firefighting activities. Data indicated that exposure levels during firefighting activities were beyond limits recommended by the Occupational Exposure Standard (OES) values. Medical tests conducted on the firefighters also indicated a considerable effect on measured medical parameters, with a significant increase in CO and decrease in NO in exhaled air of majority of the firefighters. published

Research activities focused on estimating the direct emissions of carbon from wildland fires across North America are reviewed as part of the North American Carbon Program disturbance synthesis. A comparison of methods to estimate the loss of carbon from the terrestrial biosphere to the atmosphere from wildland fires is presented. Published studies on emissions from recent and historic time periods and five specific cases are summarized, and new emissions estimates are made using contemporary methods for a set of specific fire events. Results from as many as six terrestrial models are compared. We find that methods generally produce similar results within each case, but estimates vary based on site location, vegetation (fuel) type, and fire weather. Area normalized emissions range from 0.23 kg C m−2 for shrubland sites in southern California/NW Mexico to as high as 6.0 kg C m−2 in northern conifer forests. Total emissions range from 0.23 to 1.6 Tg C for a set of 2003 fires in chaparral-dominated landscapes of California to 3.9 to 6.2 Tg C in the dense conifer forests of western Oregon. While the results from models do not always agree, variations can be attributed to differences in model assumptions and methods, including the treatment of canopy consumption and methods to account for changes in fuel moisture, one of the main drivers of variability in fire emissions. From our review and synthesis, we identify key uncertainties and areas of improvement for understanding the magnitude and spatial-temporal patterns of pyrogenic carbon emissions across North America.

Three southern Appalachian stands with sparse and unproductive pine–hardwood overstories and dense Kalmialatifolia L. understories were treated to restore productivity and diversity on steep slopes. An adaptation of the fell and burn practice was applied in summer and fall 1990. About one-half of the woody fuels were consumed at each site. A range of fire intensities was observed. Flame temperatures approached 800 °C, but the heat pulse into the forest floor only reached 60 °C at 5 cm. Humus and charred leaf litter remained on most of the surface after burning. Evidence of soil erosion was spotty and related to points of local soil disturbance. No soil left the sites. At the end of the first growing season, 23% of the burned surfaces were covered by growing plants and 62% by residual forest floor and woody debris. Felling and burning reduced evapotranspiration so that soil in the treated areas remained moister than under adjacent uncut stands. Opening the sites increased soil temperatures 2 to 5 °C at 10 cm during the first 16 months after treatment.

Smoke emissions from wildland fire can be harmful to human health and welfare, impair visibility, and contribute to greenhouse gas emissions. The generation of emissions and heat release need to be characterized to estimate the potential impacts of wildland fire smoke. This requires explicit knowledge of the source, including size of the area burned, burn period, characteristics and condition of the fuels, amount of fuel consumed, and emission factors for specific pollutants. Although errors and uncertainties arise in the process of estimating emissions, the largest errors are related to the characteristics of the fuels and amount of fuel consumed during the combustion phase. We describe the process of characterizing emissions and review the knowledge and predictive models currently available for performing the calculations. The information can be used by scientists, regulators, and land managers to improve the approach needed to define the emissions source strength for improved air quality and impact assessments.

The lack of independent, quality-assured field data prevents scientists from effectively evaluating and advancing wildland fire models. To rectify this, scientists and technicians convened in the southeastern United States in 2008, 2011 and 2012 to collect wildland fire data in six integrated core science disciplines defined by the fire modelling community. These were fuels, meteorology, fire behaviour, energy, smoke emissions and fire effects. The campaign is known as the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiment (RxCADRE) and sampled 14 forest and 14 non-forest sample units associated within 6 small replicate (,10 ha) and 10 large operational (between 10and1000ha)prescribedfires.Precampaignplanningincludedidentifyinghostingagenciesreceptivetoresearchandthe development of study, logistics and safety plans. Data were quality-assured, reduced, analysed and formatted and placed into a globally accessible repository maintained by the US Forest Service Research Data Archive. The success of the RxCADRE project led to the commencement of a follow-on larger multiagency project called the Fire and Smoke Model Evaluation Experiment (FASMEE). This overview summarises the RxCADRE project and nine companion papers that describe the data collection, analysis and important conclusions from the six science disciplines. Additional keywords: fire behaviour, fire effects, fire model evaluation, fire weather, fuel, remote-piloted aircraft system, smoke.

A lack of independent, quality-assured data prevents scientists from effectively evaluating predictions and uncertainties in fire models used by land managers. This paper presents a summary of pre-fire and post-fire fuel, fuel moisture and surface cover fraction data that can be used for fire model evaluation and development. The data were collected in the south-eastern United States on 14 forest and 14 non-forest sample units associated with 6 small replicate and 10 large operational prescribed fires conducted during 2008, 2011, and 2012 as part of the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiment (RxCADRE). Fuel loading and fuel consumption averaged 6.8 and 4.1 Mg ha–1 respectively in the forest units and 3.0 and 2.2 Mg ha–1 in the non-forest units. Post-fire white ash cover ranged from 1 to 28%. Data were used to evaluate two fuel consumption models, CONSUME and FOFEM, and to develop regression equations for predicting fuel consumption from ash cover. CONSUME and FOFEM produced similar predictions of total fuel consumption and were comparable with measured values. Simple linear models to predict pre-fire fuel loading and fuel consumption from post-fire white ash cover explained 46 and 59% of variation respectively.

Rapid Response Research is conducted during and immediately after wildland fires, in coordination with fire management teams, in order to collect information that can best be garnered in situ and in real-time. This information often includes fire behavior and fire effects data, which can be used to generate practical tools such as predictive fire models for managers. Drawing upon lessons learned from fire managers and researchers working on active wildland fires, we identify challenges including high costs, logistics, and safety; understanding and fitting into the fire management organization; building relationships with managers and other researchers; and science delivery. Our recommendations for safer and more effective Rapid Response Research are that researchers must understand the fire organizations and their objectives because a fire manager’s primary responsibility is to manage the fire safely, not support research. In addition, researchers must be prepared with equipment, a “red card” signifying sufficient training and fitness, and appropriate knowledge when arriving to do research on a fire. Further, researchers must have and follow an operations plan. We recommend using a liaison to build strong relationships with managers and sharing what was learned. Science guided by questions that are important to managers is essential to improving both the understanding of wildland fire dynamics and developing strategies to address fire risk, rehabilitation, and restoration, yet researchers must be aware of the challenges of conducting research on active wildland fires.

Knowing the amount of biomass across a landscape is becoming increasingly important to fire managers as new fuel and fire management decision support systems come on line. Fire managers rarely have the time or funding available to sample fuels operationally and often depend upon mean values for critical variables whose variation is often associated with simple stand characteristics such as age, forest type, time since last burn, stocking, or site, and other easily measured variables. This report outlines a study to collect and analyze litter and duff bulk density samples for developing a simple predictive tool to estimate forest floor fuel loading based on simple stand characteristics.

Extensive measurements of smoke exposure among wildland firefighters are summarized, showing that firefighters can be exposed to significant levels of carbon monoxide and respiratory irritants, including formaldehyde, acrolein, and respirable particulate matter. Benzene was also measured and found to be well below permissible exposure limits, with the highest concentrations occurring among firefighters working with engines and torches burning petroleum-based fuel. Exposures to all pollutants were higher among firefighters at prescribed burns than at wildfires, while shift-average smoke exposures were lowest among firefighters who performed initial attack of wildfires in the early stages of the fires. Smoke exposure reaches its highest levels among firefighters maintaining fire within designated firelines and performing direct attack of spot fires that cross firelines. These events and the associated smoke exposures were positively correlated with increasing ambient wind speeds, which hamper fire management and carry the convective plume of the fire into firefighters' breathing zone. The pollutants measured in smoke were reasonably well-correlated with each other, enabling estimation of exposure to multiple pollutants in smoke from measurements of a single pollutant such as carbon monoxide.

In recent years, wildfires have emerged as an important part of the global environment. Carbon released from fires during combustion alters the global carbon balance. Smoke emissions are a health hazard to nearby communities [Wegesser et al., 2009], can impair air quality and visibility for hundreds of kilometers downwind (Interagency Modeling of Protected Visual Environments; http://vista.cira.colostate.edu/improve/Data/IMPROVE/improve_data.htm , 2004), and contribute substantially to the global aerosol budget [van der Werf et al., 2006]. As understanding about fire as a global ecosystem process improves [Bowman et al., 2009] and as more and more global fire databases are being built [Giglio et al., 2009], wildfires are increasingly emerging as an important component of Earth system models, particularly those that involve emissions from fires and their effects on climate.

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 PM2.5 emissions and 36% uncertainty attributed to variability in emission estimating models resulted respectively in 20% and 42% ground level PM2.5 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 rate and magnitude of emissions from prescribed burns and wildfires in wildland areas throughout the world are related to biomass consumption, which is controlled by total biomass, fuel moisture, fuel distribution (fuel size and arrangement), and ignition pattern. Consequently, landuse practices, which can affect many of these components, play a crucial role in determining the rate and magnitude of smoke production from biomass burning. The variability of landuse and its relation to the magnitude and rate of smoke production, however, usually are not considered when estimating biomass emissions. For example, much prescribed wildland burning in the United States has changed from high-intensity slash burning associated with land clearing activities, in which 20 hectare fires typically emit more than 10,000 grams/second of particles within an hour or two, to low-intensity understory burning related to health management where 120 hectare fires emit less than 2,000 grams/second of particles for several hours to days. Total emissions may be similar but the duration of emissions and associated heat release rates are significantly different, causing vastly different impacts on visibility, human health, and climatic forcing. Despite changes in landuse and fire, many regional and global estimates of biomass emissions in the United States continue to assume that most emissions result from land-clearing type slash burns.

This paper reviews and summarizes literature about smoke exposure and the resulting adverse health effects among wildland firefighters Many studies have been done on this problem between 1973 and 1995 Overall the data indicate that smoke exposure at wildfires and prescribed fires is usually no more than an inconvenience, but on occasion it approaches or exceeds legal and recommended occupational exposure limits Management action is necessary to bring all smoke exposures into compliance with occupational safety regulations.

White ash results from the complete combustion of surface fuels, making it a logically simple retrospective indicator of surface fuel consumption. However, the strength of this relationship has been neither tested nor adequately demonstrated with field measurements. We measured surface fuel loads and cover fractions of white ash and four other surface materials (green vegetation, brown non-photosynthetic vegetation, black char and mineral soil) immediately before and after eight prescribed fires in four disparate fuelbed types: boreal forest floor, mixed conifer woody slash, mixed conifer understorey and longleaf pine understorey. We hypothesised that increased white ash cover should correlate significantly to surface fuel consumption. To test this hypothesis, we correlated field measures of surface fuel consumption with field measures of surface cover change. Across all four fuelbed types, we found increased white ash cover to be the only measure of surface cover change that correlated significantly to surface fuel consumption, supporting our hypothesis. We conclude that white ash load calculated from immediate post-fire measurements of white ash cover, depth and density may provide an even more accurate proxy for surface fuel consumption, and furthermore a more physically based indicator of fire severity that could be incorporated into rapid response, retrospective wildfire assessments.

Coarse woody debris serves many functions in forest ecosystem processes and has important implications for fire management as it affects air quality, soil heating and carbon budgets when it combusts. There is relatively little research evaluating the physical properties relating to the combustion of this coarse woody debris with even less specifically addressing decomposition, a condition that eventually affects all debris. We review studies evaluating the combustion and consumption of coarse woody debris in the field and under controlled conditions. The thermal properties affected by decomposition are also reviewed, as are current modelling tools to represent their combustion. Management implications and suggestions for future research are then presented.