Smoke plume dynamics involve various smoke processes and mechanics in the atmosphere and provide the scientific foundation for the development of tools to simulate and predict smoke and its environmental and human impacts. The increasing occurrence of wildfires and the demands for more extensive application of prescribed fires in the U.S. have posed great challenges and immediate actions for advancing smoke plume dynamics and improving smoke predictions and impact assessments to mitigate smoke impacts. Numerous efforts have been made recently to address these needs and challenges. This paper synthesizes advances in smoke plume dynamics research mainly conducted in the U.S. in the recent decade, identifies gaps, and suggests future research needs. The main advances include smoke data collections from comprehensive field campaigns, new satellite products, improved understanding of smoke plume properties and chemistry, structure and evolution, evaluation and improvement of smoke modeling and prediction systems, the development of coupled smoke models, and applications of machine-learning techniques. The major remaining gaps are the lack of comprehensive simultaneous measurements of smoke, fuels, fire, and atmospheric interactions during wildfires, high-resolution coupled modeling systems of these components, and real-time smoke prediction capacity. The findings from this synthesis study are expected to support smoke research and management to meet various challenges under increasing wildland fires and impacts.

AbstractSmoke plume dynamic science focuses on understanding the various smoke processes that control the movement and mixing of smoke. A current challenge facing this research is providing timely and accurate smoke information for the increasing area burned by wildfires in the western USA. This chapter synthesizes smoke plume research from the past decade to evaluate the current state of science and identify future research needs. Major advances have been achieved in measurements and modeling of smoke plume rise, dispersion, transport, and superfog; interactions with fire, atmosphere, and canopy; and applications to smoke management. The biggest remaining gaps are the lack of high-resolution coupled fire, smoke, and atmospheric modeling systems, and simultaneous measurements of these components. The science of smoke plume dynamics is likely to improve through development and implementation of: improved observational capabilities and computational power; new approaches and tools for data integration; varied levels of observations, partnerships, and projects focused on field campaigns and operational management; and new efforts to implement fire and stewardship strategies and transition research on smoke dynamics into operational tools. Recent research on a number of key smoke plume dynamics has improved our understanding of coupled smoke modeling systems, modeling tools that use field campaign data, real-time smoke modeling and prediction, and smoke from duff burning. This new research will lead to better predictions of smoke production and transport, including the influence of a warmer climate on smoke.

This presentation describes a Joint Fire Science Program project awarded in 2008 under the task of smoke and emissions models evaluation, presents results obtained so far, and seeks potential application and collaboration opportunities. Regional smoke and air quality models require plume rise information as initial and boundary conditions in modeling point-source emissions like wildland fires. A unrealistic specification of plume rise will lead to incorrect simulation and prediction in smoke transport and dispersion and spatial patterns of regional pollutant distribution. This proposed study was to evaluate and improve Daysmoke, a plume rise model, and to understand the significance for regional smoke and air quality modeling. The research objectives included evaluating plume rise estimates from Daysmoke and comparing with other models using field measurements, improving accuracy and feasibility of Daysmoke, evaluating and analyzing uncertainty in regional smoke and air quality modeling due to plume rise calculation, and transferring research products into field application tools. A combined approach of field measurement, numerical modeling, and dynamical and statistical analysis would be used to obtain data, conduct simulation and evaluation, and improve model. The expected products include datasets of smoke measurements (plume rise, vertical profiles of smoke particles, ground PM2.5, smoke plume satellite remote sensing, and meteorological conditions), evaluation and improvement of Daysmoke, uncertainty analysis of regional smoke and air quality modeling, and Web and GIS supported Daysmoke. These products would to provide fire and air quality managers and modelers with quantitative information and tools for understanding the accuracy, limits, and uncertainty in plume rise calculation, and their impacts on simulation and prediction of regional smoke transport and air quality effects. During the first year of this project, plume rise was measured for 11 burns with a ceilometer, the MODIS and GOES satellite remote sensing images were collected, ground PM2.5 concentrations were measured for four burns by a research group from University of Georgia, and the Calsmoke software interface was developed.

This study applied the Model of Acidification of Groundwater in Catchments (MAGIC) to estimate the sensitivity of 66 watersheds in the Southern Blue Ridge Province of the Southern Appalachian Mountains, United States, to changes in atmospheric sulfur (S) deposition. MAGIC predicted that stream acid neutralizing capacity (ANC) values were above 20 μeq/L in all modeled watersheds in 1860. Hindcast simulations suggested that the median historical acidification of the modeled streams was a loss of about 25 μeq/L of ANC between 1860 and 2005. Although the model projected substantial changes in soil and stream chemistry since pre-industrial times, simulated future changes in response to emission controls were small. Results suggested that modeled watersheds would not change to a large degree with respect to stream ANC or soil % base saturation over the next century in response to a rather large decrease in atmospheric S deposition. Nevertheless, the magnitude of the relatively small simulated future changes in stream and soil chemistry depended on the extent to which S emissions are reduced. This projection of minimal recovery in response to large future S emissions reductions is important for designing appropriate management strategies for acid-impacted water and soil resources. Exploratory analyses were conducted to put some of the major modeling uncertainties into perspective.

An important tool in the evaluation of acidification damage to aquatic and terrestrial ecosystems is the critical load (CL), which represents the steady-state level of acidic deposition below which ecological damage would not be expected to occur, according to current scientific understanding. A deposition load intended to be protective of a specified resource condition at a particular point in time is generally called a target load (TL). The CL or TL for protection of aquatic biota is generally based on maintaining surface water acid neutralizing capacity (ANC) at an acceptable level. This study included calibration and application of the watershed model MAGIC (Model of Acidification of Groundwater in Catchments) to estimate the target sulfur (S) deposition load for the protection of aquatic resources at several future points in time in 66 generally acid-sensitive watersheds in the southern Blue Ridge province of North Carolina and two adjoining states. Potential future change in nitrogen leaching is not considered. Estimated TLs for S deposition ranged from zero (ecological objective not attainable by the specified point in time) to values many times greater than current S deposition depending on the selected site, ANC endpoint, and evaluation year. For some sites, one or more of the selected target ANC critical levels (0, 20, 50, 100 μeq/L) could not be achieved by the year 2100 even if S deposition was reduced to zero and maintained at that level throughout the simulation. Many of these highly sensitive streams were simulated by the model to have had preindustrial ANC below some of these target values. For other sites, the watershed soils contained sufficiently large buffering capacity that even very high sustained levels of atmospheric S deposition would not reduce stream ANC below common damage thresholds.

Daysmoke is a local smoke transport model and has been used to provide smoke plume rise information. It includes a large number of parameters describing the dynamic and stochastic processes of particle upward movement, fallout, fluctuation, and burn emissions. This study identifies the important parameters for Daysmoke simulations of plume rise and seeks to understand their impacts on regional air quality simulations with the Community Multiscale Air Quality (CMAQ) model. The Fourier Amplitude Sensitivity Test (FAST) was first applied to Daysmoke simulations of prescribed burning in the southeastern U.S. It is shown that, for the specified value ranges of 15 parameters, entrainment coefficient and number of updraft cores are the most important for determining smoke plume rise. Initial plume temperature anomaly, diameter of flaming area, and thermal stability also contribute to a certain extent. CMAQ simulations were then conducted for a couple of different updraft core numbers. The simulated ground PM2.5 concentration is much closer to the measurements with multiple updraft cores than single core. The results from this study therefore suggest that simulations of Daysmoke and CMAQ could be improved by a better understanding of plume structure to aid in specifying the number of smoke updraft cores.

This study investigates smoke incursion into urban areas by examining a prescribed burn in central Georgia, USA, on 28 February 2007. Simulations were conducted with a regional modeling framework to understand transport, dispersion, and structure of smoke plumes, the air quality effects, sensitivity to emissions, and the roles of burn management strategy in mitigating the effects. The results indicate that smoke plumes first went west, but turned north-west at noon owing to a shift in wind direction. The smoke then invaded metropolitan Atlanta during the evening rush hour. The plumes caused severe air quality problems in Atlanta. Some hourly ground PM2.5 (particulate matter not greater than 2.5 μm in diameter) concentrations at three metropolitan Atlanta locations were three to four times as high as the daily (24-h) US National Ambient Air Quality Standard. The simulated shift in the smoke transport direction and the resultant effects on air quality are supported by the satellite and ambient air measurements. Two sensitivity simulations indicate a nearly linear relation between the emission intensities and PM2.5 concentrations. Two other simulations indicate that the impacts on air quality for the residents of Atlanta during the evening commute could have been reduced if the starting time of the burn had been altered.

On February 28, 2007, a severe smoke event caused by prescribed forest fires occurred in Atlanta, GA. Later smoke events in the southeastern metropolitan areas of the United States caused by the Georgia-Florida wild forest fires further magnified the significance of forest fire emissions and the benefits of being able to accurately predict such occurrences. By using preburning information, we utilize an operational forecasting system to simulate the potential air quality impacts from two large February 28th fires. Our "forecast" predicts that the scheduled prescribed fires would have resulted in over 1 million Atlanta residents being potentially exposed to fine particle matter (PM2.5) levels of 35 microg m(-3) or higher from 4 p.m. to midnight. The simulated peak 1 h PM2.5 concentration is about 121 microg m(-3). Our study suggests that the current air quality forecasting technology can be a useful tool for helping the management of fire activities to protect public health. With postburning information, our "hindcast" predictions improved significantly on timing and location and slightly on peak values. "Hindcast" simulations also indicated that additional isoprenoid emissions from pine species temporarily triggered by the fire could induce rapid ozone and secondary organic aerosol formation during late winter. Results from this study suggest that fire induced biogenic volatile organic compounds emissions missing from current fire emissions estimate should be included in the future.

We utilize Hi-Res, a regional forecasting system which provides local air quality forecasts for the metro Atlanta area since 2006, to predict the air quality impacts from wildland fires. As extensions to the Hi-Res system, the Consume and FEPS models are used to estimate the fire emissions from potential fire events. Brute-force or DDM methods are used to calculate the air quality contributions from the fires. We have tested this tool to predict air quality impacts from Jasper County prescribed fires on February 28, 2007 and the Georgia-Florida wildfires which occurred during April-May, 2007.