Abstract  Smoke from human-induced fires such as prescribed fires can occasionally cause significant reduction in visibility on highways in the southern United States. Visibility reduction to less than 3 m has been termed "superfog" and environmental conditions that lead to its formation have been proposed previously. Accurate characterization and prediction of precursor conditions for superfog is needed to prevent dangerous low visibility situations when planning prescribed fires. It is hypothesized that extremely hygroscopic cloud condensation nuclei from the smoldering phase of a fire can produce a large number of droplets smaller in size than in naturally occurring fog. This large number of small droplets can produce superfog conditions with relatively low liquid water content. A thermodynamics-based model for fog formation was developed. Laboratory generated superfog measured by a Phase Doppler Particle Analyzer determined that mean droplet radius was 1.5 mu m and the size distribution could be modeled with a lognormal distribution. Experiments in an environmentally-conditioned wind tunnel using longleaf pine (Pinus palustris Mill.) needle fuel beds provided visibility, heat flux, temperature, humidity, and particle data for model validation. Numerical modeling was used to approximate the growth of a superfog boundary-layer with liquid water content values of 2 g m(-3) or greater. The model successfully predicted previous superfog events.

Abstract  BACKGROUND: The increasing size and frequency of wildland fires are leading to greater potential for cardiopulmonary disease and cancer in exposed populations; however, little is known about how the types of fuel and combustion phases affect these adverse outcomes.

OBJECTIVES: We evaluated the mutagenicity and lung toxicity of particulate matter (PM) from flaming vs. smoldering phases of five biomass fuels, and compared results by equal mass or emission factors (EFs) derived from amount of fuel consumed.

METHODS: A quartz-tube furnace coupled to a multistage cryotrap was employed to collect smoke condensate from flaming and smoldering combustion of red oak, peat, pine needles, pine, and eucalyptus. Samples were analyzed chemically and assessed for acute lung toxicity in mice and mutagenicity in Salmonella.

RESULTS: The average combustion efficiency was 73 and 98% for the smoldering and flaming phases, respectively. On an equal mass basis, PM from eucalyptus and peat burned under flaming conditions induced significant lung toxicity potencies (neutrophil/mass of PM) compared to smoldering PM, whereas high levels of mutagenicity potencies were observed for flaming pine and peat PM compared to smoldering PM. When effects were adjusted for EF, the smoldering eucalyptus PM had the highest lung toxicity EF (neutrophil/mass of fuel burned), whereas smoldering pine and pine needles had the highest mutagenicity EF. These latter values were approximately 5, 10, and 30 times greater than those reported for open burning of agricultural plastic, woodburning cookstoves, and some municipal waste combustors, respectively.

CONCLUSIONS: PM from different fuels and combustion phases have appreciable differences in lung toxic and mutagenic potency, and on a mass basis, flaming samples are more active, whereas smoldering samples have greater effect when EFs are taken into account. Knowledge of the differential toxicity of biomass emissions will contribute to more accurate hazard assessment of biomass smoke exposures.

Abstract  The low-cost and compact size of light-scattering-based particulate matter (PM) sensors provide an opportunity for improved spatiotemporally resolved PM measurements. However, these inexpensive sensors have limitations and need to be characterized under realistic conditions. This study evaluated two Plantower PMS (particulate matter sensor) 1003s and two PMS 5003s outdoors in Salt Lake City, Utah over 320 days (1/2016-2/2016 and 12/2016-10/2017) through multiple seasons and a variety of elevated PM2.5 events including wintertime cold-air pools (CAPs), fireworks, and wildfires. The PMS 1003/5003 sensors generally tracked PM2.5 concentrations compared to co-located reference air monitors (one tapered element oscillating microbalance, TEOM, and one gravimetric federal reference method, FRM). The different PMS sensor models and sets of the same sensor model exhibited some intra-sensor variability. During winter 2017, the two PMS 1003s consistently overestimated PM2.5 by a factor of 1.89 (TEOM PM2.5<40 μg/m3). However, compared to the TEOM, one PMS 5003 overestimated PM2.5 concentrations by a factor of 1.47 while the other roughly agreed with the TEOM. The PMS sensor response also differed by season. In two consecutive winters, the PMS PM2.5 measurements correlated with the hourly TEOM measurements (R2 > 0.87) and 24-h FRM measurements (R2 > 0.88) while in spring (March-June) and wildfire season (June-October) 2017, the correlations were poorer (R2 of 0.18-0.32 and 0.48-0.72, respectively). The PMS 1003s maintained high intra-sensor agreement after one year of deployment during the winter seasons, however, one PMS 1003 sensor exhibited a significant drift beginning in March 2017 and continued to deteriorate through the end of the study. Overall, this study demonstrated good correlations between the PMS sensors and reference monitors in the winter season, seasonal differences in sensor performance, some intra-sensor variability, and drift in one sensor. These types of factors should be considered when using measurements from a network of low-cost PM sensors.

Abstract  Past and current forest management affects wildland fire smoke impacts on downwind human populations. However, mismatches between the scale of benefits and risks make it difficult to proactively manage wildland fires to promote both ecological and public health. Building on recent literature and advances in modeling smoke and health effects, we outline a framework to more directly quantify and compare smoke impacts based on emissions, dispersion, and the size and vulnerability of downwind populations across time and space. We apply the framework in a case study to demonstrate how different kinds of fires in California's Central Sierra Nevada have resulted in very different smoke impacts. Our results indicate that the 257,314-acre Rim Fire of 2013 probably resulted in 7 million person-days of smoke impact across California and Nevada, which was greater than 5 times the impact per burned unit area than two earlier wildfires, Grouse and Harden of 2009, that were intentionally managed for resource objectives within the same airshed. The framework and results suggest strategies and tactics for undertaking larger-scale burns that can minimize smoke impacts, restore forest ecosystems, and reduce the potential for more hazardous wildfire and smoke events.

Abstract  BACKGROUND: The effects of exposure to fine particulate matter ([Formula: see text]) during wildland fires are not well understood in comparison with [Formula: see text] exposures from other sources.

OBJECTIVES: We examined the cardiopulmonary effects of short-term exposure to [Formula: see text] on smoke days in the United States to evaluate whether health effects are consistent with those during non-smoke days.

METHODS: We examined cardiopulmonary hospitalizations among adults [Formula: see text] y of age, in U.S. counties ([Formula: see text]) within [Formula: see text] of 123 large wildfires during 2008-2010. We evaluated associations during smoke and non-smoke days and examined variability with respect to modeled and observed exposure metrics. Poisson regression was used to estimate county-specific effects at lag days 0-6 (L0-6), adjusted for day of week, temperature, humidity, and seasonal trend. We used meta-analyses to combine county-specific effects and estimate overall percentage differences in hospitalizations expressed per [Formula: see text] increase in [Formula: see text].

RESULTS: Exposure to [Formula: see text], on all days and locations, was associated with increased hospitalizations on smoke and non-smoke days using modeled exposure metrics. The estimated effects persisted across multiple lags, with a percentage increase of 1.08% [95% confidence interval (CI): 0.28, 1.89] on smoke days and 0.67% (95% CI: [Formula: see text], 1.44) on non-smoke days for respiratory and 0.61% (95% CI: 0.09, 1.14) on smoke days and 0.69% (95% CI: 0.19, 1.2) on non-smoke days for cardiovascular outcomes on L1. For asthma-related hospitalizations, the percentage increase was greater on smoke days [6.9% (95% CI: 3.71, 10.11)] than non-smoke days [1.34% (95% CI: [Formula: see text], 3.77)] on L1.

CONCLUSIONS: The increased risk of [Formula: see text]-related cardiopulmonary hospitalizations was similar on smoke and non-smoke days across multiple lags and exposure metrics, whereas risk for asthma-related hospitalizations was higher during smoke days. https://doi.org/10.1289/EHP3860.

Abstract  Increases in large wildfire frequency and intensity and a longer fire season in the western United States are resulting in a significant increase in air pollution, including concentrations of PM2.5 (particulate matter <2.5 µm in aerodynamic diameter) that pose significant health risks to nearby communities. During wildfires, government agencies monitor PM2.5 mass concentrations providing information and actions needed to protect affected communities; this requires continuously measuring instruments. This study assessed the performance of seven candidate instruments: (1) Met One Environmental beta attenuation monitor (EBAM), (2) Met One ES model 642 (ES642), (3) Grimm Environmental Dust Monitor 164 (EDM), (4) Thermo ADR 1500 (ADR), (5) TSI DRX model 8543 (DRX), (6) Dylos 1700 (Dylos), and (7) Purple Air II (PA-II) in comparison with a BAM 1020 (BAM) reference instrument. With the exception of the EBAM, all candidates use light scattering to determine PM2.5 mass concentrations. Our comparison study included environmental chamber and field components, with two of each candidate instrument operating next to the reference instrument. The chamber component involved 6 days of comparisons for biomass combustion emissions. The field component involved operating all instruments in an air monitoring station for 39.5 days with hourly average relative humidity (RH) ranging from 19% to 98%. Goals were to assess instrument precision and accuracy and effects of RH, elemental carbon (EC), and organic carbon (OC) concentrations. All replicate candidate instruments showed high hourly correlations (R2 ≥ 0.80) and higher daily average correlations (R2 ≥ 0.90), where all instruments correlated well (R2 ≥ 0.80) with the reference. The DRX and Purple Air overestimated PM2.5 mass concentrations by a factor of ~two. Differences between candidates and reference were more pronounced at higher PM2.5 concentrations. All optical instruments were affected by high RH and by the EC/OC ratio. Equations to convert candidate instruments data to FEM BAM type data are provided to enhance the usability of data from candidate instruments. Implications: This study tested the performance of seven candidate PM2.5 mass concentration measuring instruments in two settings - environmental chamber and field. The instruments were tested to determine their suitability for use during biomass combustion events and the effects of RH, PM mass concentrations, and concentrations of EC and OC on their performance. The accuracy and precision of each monitor and effect of RH, PM concentration, EC and OC concentrations are varied. The data show that most of these candidate instruments are suitable for measuring PM2.5 concentration during biomass combustions with a proper correction factor for each instrument type.

Abstract  Spatially explicit burn probability modeling is increasingly applied to assess wildfire risk and inform mitigation strategy development. Burn probabilities are typically expressed on a per-pixel basis, calculated as the number of times a pixel burns divided by the number of simulation iterations. Spatial intersection of highly valued resources and assets (HVRAs) with pixel-based burn probability estimates enables quantification of HVRA exposure to wildfire in terms of expected area burned. However, statistical expectations can mask variability in HVRA area burned across all simulated fires. We present an alternative, polygon-based formulation for deriving estimates of HVRA area burned. This effort enhances investigations into spatial patterns of fire occurrence and behavior by overlaying simulated fire perimeters with mapped HVRA polygons to estimate conditional distributions of HVRA area burned. This information can be especially useful for assessing risks where cumulative effects and the spatial pattern and extent of area burned influence HVRA response to fire. We illustrate our modeling approach and demonstrate application across real-world landscapes for two case studies: first, a comparative analysis of exposure and area burned across ten municipal watersheds on the Beaverhead-Deerlodge National Forest in Montana, USA, and second, fireshed delineation and exposure analysis of a geographically isolated and limited area of critical wildlife habitat on the Pike and San Isabel National Forests in Colorado, USA. We highlight how this information can be used to inform prioritization and mitigation decisions and can be used complementarily with more traditional pixel-based burn probability and fire intensity metrics in an expanded exposure analysis framework.

Abstract  Severe and persistent 21st-century drought in southwestern North America (SWNA) motivates comparisons to medieval megadroughts and questions about the role of anthropogenic climate change. We use hydrological modeling and new 1200-year tree-ring reconstructions of summer soil moisture to demonstrate that the 2000-2018 SWNA drought was the second driest 19-year period since 800 CE, exceeded only by a late-1500s megadrought. The megadrought-like trajectory of 2000-2018 soil moisture was driven by natural variability superimposed on drying due to anthropogenic warming. Anthropogenic trends in temperature, relative humidity, and precipitation estimated from 31 climate models account for 47% (model interquartiles of 35 to 105%) of the 2000-2018 drought severity, pushing an otherwise moderate drought onto a trajectory comparable to the worst SWNA megadroughts since 800 CE.

Abstract  LANDFIRE is the working name given to the Landscape Fire and Resource Management Planning Tools Project (http://www.landfire.gov). The project was initiated in response to mega-fires and the need for managers to have consistent, wall-to-wall (i.e., all wildlands regardless of agency/ownership), geospatial data, on vegetation, fuels, and terrain to support use of fire behavior and effects prediction systems in guiding policy and management decisions. Base layers were created in a 5-year program of research and development ending in 2009, with processes in place to periodically update fuel and vegetation layers in response to anthropogenic and natural disturbances. LANDFIRE has been institutionalized as the primary data source for modeling activities aimed at meeting the goals of the United States' National Cohesive Wildland Fire Management Strategy, and the data are available on-line to any user for conducting landscape analyses. Data access and use are high and expected to grow with the increasing scope and complexity of wildland fire management, thus requiring continued LANDFIRE improvements and updates.

Abstract  Mechanical fuel treatments are increasingly being used for wildfire hazard reduction in the western U.S. However, the efficacy of these treatments for reducing wildfire hazard at a landscape scale is difficult to quantify, especially when including growth following treatment. A set of uneven- and even-aged treatments designed to reduce fire hazard were simulated on 0.8 million hectares of timberland in Colorado. Wildfire hazard ratings using torching and crowning indices were developed: stands were selected for treatment: treatment was simulated and hazard ratings were reassessed. The results show that the even-aged treatments initially place more area within our hazard thresholds than do the uneven-aged treatments and that the uneven-aged treatment that removes more small stems reduces risk more than the treatment removing more large stems. The treatment costs follow the same pattern, with the even-aged treatments costing least. However, potential revenues are, as expected, higher for the uneven-aged large treatment. The results also show that both higher costs and higher revenues accrue to the treatments applied to the higher risk stands. Treatments also have differing risk reductions depending on the initial risk category. Even without considering growth or revenues, the outcomes of a state-level treatment program are difficult to estimate. This implies that at a minimum, forest-level, if not state-level analyses including overall measures of risk reduction, costs, revenues and long-term effects need to be conducted in concert with setting priorities for treating timberlands.

Abstract  A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions-cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R-2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment.

Abstract  Since the publication of the compilation of biomass burning emission factors by Andreae and Merlet (2001), a large number of studies have greatly expanded the amount of available data on emissions from various types of biomass burning. Using essentially the same methodology as Andreae and Merlet (2001), this paper presents an updated compilation of emission factors. The data from over 370 published studies were critically evaluated and integrated into a consistent format. Several new categories of biomass burning were added, and the number of species for which emission data are presented was increased from 93 to 121. Where field data are still insufficient, estimates based on appropriate extrapolation techniques are proposed. For key species, the updated emission factors are compared with previously published values. Based on these emission factors and published global activity estimates, I have derived estimates of pyrogenic emissions for important species released by the various types of biomass burning.

Abstract  The Flint Hills of eastern Kansas and northern Oklahoma is home to the largest remaining contiguous grassland prairie in the United States. Throughout the prairie, burning is a common practice used to preserve the prairie from encroachment of woody species such as eastern Red Cedar, and to enhance the quantity and quality of the grass grown for cattle grazing in the region. However, widespread annual burning in early spring has led to air quality exceedances and pollution impacts in urban areas such as Kansas City, Topeka, and Wichita. Our research effort focuses on developing a modelling environment that simulates the effects of burning in the Flint Hills using an integrated modeling system, including an eco-hydrological model, an air quality and dispersion model, an economic and health effects model, and a terrestrial-species model. Using this integrated system, we can model historical burning practices as well as hypothetical variations in timing and quantity of burns. Then, we can investigate the relative trade-offs between farm productivity, ecological effects, urban health effects, and habitat diversity for terrestrial species given different burning scenarios. The results from this systems approach will provide land managers with information about the relative trade-offs associated with burning considering multiple elements of sustainability throughout the Flint Hills.

Abstract  Weights and volumes of downed woody material in diameter classes of one-fourth to 1, 1 to 3, and greater than 3 inches and forest floor duff depths were summarized from extensive inventories in nothern Idaho and Montana. Biomass loadings are shown by cover types and habitat types within National Forests. Total downed woody biomass ranged from 5 tons per acre in ponderosa pine to 33 tons per acre in cedar-hemlock. Loadings generally increased with increased productivity, but varied greatly with stand age. Fuels tended to become predictably high in overmature stands but unpredictable in young, immature, and mature stands. Forest fuel succession is discussed in relation to tree mortality, fuel buildup, and depletion.

Abstract  These methods for measuring ambient concentrations of specified air pollutants have been designated as "reference methods" or "equivalent methods" in accordance with Title 40, Part 53 of the Code of Federal Regulations (40 CFR Part 53). Subject to any limitations (e.g., operating range or temperature range) specified in the applicable designation, each method is acceptable for use in state or local air quality surveillance systems under 40 CFR Part 58 unless the applicable designation is subsequently canceled. Automated methods for pollutants other than PM10 are acceptable for use only at shelter temperatures between 20°C and 30°C and line voltages between 105 and 125 volts unless wider limits are specified in the method description. Prospective users of the methods listed should note (1) that each method must be used in strict accordance with its associated operation or instruction manual and with applicable quality assurance procedures, and (2) that modification of a method by its vendor or user may cause the pertinent designation to be inapplicable to the method as modified. (See Section 2.8 of Appendix C, 40 CFR Part 58 for approval of modifications to any of these methods by users.) Further information concerning particular designations may be found in the Federal Register notice cited for each method or by writing to the Center for Environmental Measurements and Modeling, Air Methods and Characterization Division (MD-D205-03), U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711. Technical information concerning the methods should be obtained by contacting the source listed for each method. Source addresses are listed at the end of the listing of methods, except for the addresses for lead method sources, which are given with the method. New analyzers or PM10 samplers sold as reference or equivalent methods must carry a label or sticker identifying them as designated methods. For analyzers or PM10 samplers sold prior to the designation of a method with the same or similar model number, the model number does not necessarily identify an analyzer or sampler as a designated method. Consult the manufacturer or seller to determine if a previously sold analyzer or sampler can be considered a designated method or if it can be upgraded to designation status. Analyzer users who experience operational or other difficulties with a designated analyzer or sampler and are unable to resolve the problem directly with the instrument manufacturer may contact EPA (preferably in writing) at the above address for assistance. This list will be revised as necessary to reflect any new designations, modifications of existing designations, or any cancellation of a designation currently in effect. The most current revision of the list will be available for inspection at EPA's Regional Offices, and copies may be obtained at the Internet site identified above or by writing to the Center for Environmental Measurements and Modeling at the address specified above.

Abstract  Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e. g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Except for slope, none of the other topographic characteristics can be calculated until the flow direction at each pixel within a DEM is determined. However, flow direction cannot be accurately calculated until depressions and flat areas within a DEM have been rectified. This is a routine problem in hydrologic modeling, because virtually all DEMs contain flat and sink pixels, both real and artifactual, that if left untreated will prevent accurate simulation of hydrologic flow paths. Although a number of algorithms are available for rectifying flat and sink pixels in DEM data, treatment of flat areas and depressions and calculation of flow direction remain problematic for reasons of complexity and uncertainty. A new algorithm that effectively rectifies flat and sink pixels was developed and tested. The approach is to use linear interpolation between low elevation grid cells on the edge of each flat area or depression defined as outlets and higher elevation grid cells on the opposite side defined as inflow pixels. The implementation requires an iterative solution to accommodate the irregular geometry of flat areas or depressions and exceptions that arise. Linear interpolation across flat areas or depressions provides a natural way to scale elevation adjustments based on the vertical scale of the surrounding topography, thereby avoiding the addition or subtraction of arbitrary small numbers that we regard as a disadvantage in some prior techniques. Tests for two virtual terrains and one real terrain show that our algorithm effectively rectifies flat areas and depressions, even in low-relief terrain, and produces realistic patterns of flow accumulation and extracted channel networks.

Abstract  We estimate the value of three types of information about fire risk to a nonindustrial forest landowner: the relationship between fire arrival rates and stand age, the magnitude of fire arrival rates, and the efficacy of fuel reduction treatment. Our model incorporates planting density and the level and timing of fuel reduction treatment as landowner decisions. These factors affect, among other things, the loss a landowner incurs should fire arrive before harvesting. The value of information depends on the nature and combination of mistakes a landowner makes, the relationship between fire arrival and stand age, and on whether the landowner undertakes fuel treatment and values nontimber benefits. Information of various types is of most value to a landowner who does not undertake fuel treatment. The value of information about the magnitude of fire risk is also more than twice as high when the landowner underestimates fire risk, rather than overestimating it. For a landowner who undertakes fuel treatment but makes multiple mistakes, the asymmetry between overestimating and underestimating fire risk and efficacy of fuel reduction is even more pronounced.

Abstract  Fire is both a natural and anthropogenic disturbance influencing the distribution, structure, and functioning of terrestrial ecosystems around the world. Many plants and animals depend on fire for their continued existence. Others species, such as rainforest plants species, are extremely intolerant of burning and need protection from fire. The properties of a fire regime are changing as the natural world’s landscapes become fragmented and human influence becomes pervasive. A sound understanding of fire and its effects on ecosystems is an essential prerequisite for effectively managing this widespread ecological process.

Abstract  The concept of Final Ecosystem Goods and Services (FEGS) explicitly connects ecosystem services to the people that benefit from them. This report presents a number of practical strategies for incorporating FEGS, and more broadly ecosystem services, into the decision-making process. Whether a decision process is in early or late stages, or whether a process includes informal or formal decision analysis, there are multiple points where ecosystem services concepts can be integrated. This report uses Structured Decision Making (SDM) as an organizing framework to illustrate the role ecosystem services can play in a values-focused decision-process, including: • Clarifying the decision context: Ecosystem services can help clarify the potential impacts of an issue on natural resources together with their spatial and temporal extent based on supply and delivery of those services, and help identify beneficiaries for inclusion as stakeholders in the deliberative process. • Defining objectives and performance measures: Ecosystem services may directly represent stakeholder objectives, or may be means toward achieving other objectives. • Creating alternatives: Ecosystem services can bring to light creative alternatives for achieving other social, economic, health, or general well-being objectives. • Estimating consequences: Ecosystem services assessments can implement ecological production functions (EPFs) and ecological benefits functions (EBFs) to link decision alternatives to stakeholder objectives. • Considering trade-offs: The decision process should consider ecosystem services objectives alongside other kinds of objectives (e.g., social, economic) that may or may not be related to ecosystem conditions. • Implementing and monitoring: Monitoring after a decision is implemented can help determine whether the incorporation of ecosystem services leads to measurable benefits, or what levels of ecosystem function are needed for meaningful change. An evaluation of impacts on ecosystem services from past decisions can provide a learning opportunity to adapt future decisions. Each chapter of this report details one of these steps, and each chapter is paired with a set of appendices providing examples of tools and approaches that decision makers can use for that step. This report also presents a number of case study examples that illustrate the ecosystem services concepts, approaches, and tools presented in this report for a variety of community decision processes, such as resiliency planning or sustainability planning, watershed or coastal management, habitat restoration, risk assessments, or environmental impact assessments. Possible advantages of integrating ecosystem services concepts into community decision-making through values-focused thinking include: improved information collection, improved communication, expanded stakeholder engagement, creative development and evaluation of alternatives, interconnected decisions, and strategic thinking.

Abstract  This paper assesses existing research on the effectiveness of hazardous fuel reduction in changing wildfire behavior. Over two years, we reviewed more than 250 papers that evaluated three types of fuel treatment in relation to fire behavior in western forests – prescribed fire, mechanical thinning, and a combination of thinning and burning. We also surveyed the literature to evaluate recent suggestions by policy makers that commercial logging can be used to treat dense forest fuels. This assessment focused on ponderosa pine – a “fire adapted” forest type where periodic, low-intensity fires were the ecological norm in presettlement times. Nonetheless, studies in other forest types were reviewed if the research provided useful information on the relationship between fuel treatments and fire behavior.