Fire Smoke Transport Research Articles

Evidence for Wildland Fire Smoke Transport of Microbes From Terrestrial Sources to the Atmosphere and Back

AbstractSmoke from wildland fires contains more diverse, viable microbes than typical ambient air, yet little is known about the sources and sinks of smoke‐borne microorganisms. Data from molecular‐based surveys suggest that smoke‐borne microorganisms originate from material associated with the vegetation and underlying soils that becomes aerosolized during combustion, however, the sources of microbes in smoke have not yet been experimentally assessed. To elucidate this link, we studied high‐intensity forest fires in the Fishlake National Forest, Utah, USA and applied source‐sink modeling to assemblages of 16S ribosomal RNA (rRNA) gene sequences recovered from samples of smoke, vegetation, and soil. Our results suggest that 70% of the bacterial taxa in smoke originated from the local aspen (Populus tremuloides) (33%) and soil (37%) communities. In comparison, 42% of bacteria in air sampled prior to the fires could be attributed to these terrestrial sources. When the bacterial assemblages in smoke were modeled as sources to the local communities, they contributed an average of 25% to the terrestrial sinks versus an estimated contribution of <4% from ambient air. Our results provide support for the role of wildland fire in bacterial dispersal and the working hypothesis that smoke is an environmental reservoir of microbes for receiving ecosystems.

Sensitivity Analysis of Influencing Factors of Fire Smoke Transport on Subway Station Platforms

Sensitivity Analysis of Influencing Factors of Fire Smoke Transport on Subway Station Platforms

The effect of fire location and the reverse stack on fire smoke transport in high-rise buildings

In this paper, smoke transport in high-rise buildings through elevator shafts and stairwells is investigated for various fire location and stack effect conditions. For this purpose, a transient network model, Fire-STORM, is upgraded and used. The results are benchmarked by using a computational fluid dynamics (CFD) model. Six scenarios are tested, which are 1st floor, mid-floor, and top-most floor fires under normal stack (cold environment) and reverse stack (hot environment) conditions. For each scenario, the time history of pressures, temperatures, and soot mass fractions in the fire floors, elevator shafts, and stairwells and the average soot mass fraction in all stories of the building are presented. Overall, Fire-STORM has reasonably good accuracy compared to CFD with significantly faster computation times (90 s on a single core vs. 4 days on 32 cores in parallel). One of the intended uses of this fast low-order model is a data generation engine for neural network modeling of high-rise building fires. As such, one of the unique features of this work is the development of a realistic random heat release rate (HRR) modeling approach created using a Gaussian process.

Machine Learning-Based Integration of High-Resolution Wildfire Smoke Simulations and Observations for Regional Health Impact Assessment.

Large wildfires are an increasing threat to the western U.S. In the 2017 fire season, extensive wildfires occurred across the Pacific Northwest (PNW). To evaluate public health impacts of wildfire smoke, we integrated numerical simulations and observations for regional fire events during August-September of 2017. A one-way coupled Weather Research and Forecasting and Community Multiscale Air Quality modeling system was used to simulate fire smoke transport and dispersion. To reduce modeling bias in fine particulate matter (PM2.5) and to optimize smoke exposure estimates, we integrated modeling results with the high-resolution Multi-Angle Implementation of Atmospheric Correction satellite aerosol optical depth and the U.S. Environmental Protection Agency AirNow ground-level monitoring PM2.5 concentrations. Three machine learning-based data fusion algorithms were applied: An ordinary multi-linear regression method, a generalized boosting method, and a random forest (RF) method. 10-Fold cross-validation found improved surface PM2.5 estimation after data integration and bias correction, especially with the RF method. Lastly, to assess transient health effects of fire smoke, we applied the optimized high-resolution PM2.5 exposure estimate in a short-term exposure-response function. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 183 (95% confidence interval: 0, 432), with 85% of the PM2.5 pollution and 95% of the consequent multiple-cause mortality contributed by fire emissions. This application demonstrates both the profound health impacts of fire smoke over the PNW and the need for a high-performance fire smoke forecasting and reanalysis system to reduce public health risks of smoke hazards in fire-prone regions.

Fire Smoke Transport and Opacity Reduced-Order Model (Fire-STORM): A New Computer Model for High-Rise Fire Smoke Simulations

The problem of smoke spread through elevator shafts in high rise buildings is analyzed theoretically and numerically in this paper. While experiments and computational fluid dynamics (CFD) models have been used for such exercises, there is a need for fast reduced-order models for such scenarios. Towards this goal, a transient network model called High-rise fire smoke transport and opacity reduced-order model (Fire-STORM) was developed to investigate heat and mass transfer through the elevator shaft during fires. The model numerically solves the coupled set of differential equations of the fire floor in conjunction with the steady state conservation equations of the elevator shaft. The model is validated in two stages. First, the stack effect in a non-fire scenario is analyzed. Pressure differences through exterior doors and elevator doors are compared with experimental data available in the literature and results of a computational fluid dynamics tool. Then, a first-floor fire scenario is considered for the same high-rise building in four different cases which are combinations of different building tightness and ambient temperatures. The results are compared with CFD simulations. For the four different building envelope and ambient thermal conditions, the soot mass fractions and optical visibilities were calculated and compared to CFD predictions. Overall, Fire-STORM is a simple and fast tool to model the evolution of heat and mass transfer in a high-rise building affected by fire. While Fire-STORM is excellent in predicting transient smoke transport for buildings with loose envelopes, it should be used with caution for buildings with tight envelopes since the errors for these cases are relatively high. Despite this, the relative computational speed difference between Fire-STORM and the CFD model highlights the utility of a reduced-order model for firefighter decision making and building control system design.

Multiple steady states of fire smoke transport in a multi-branch tunnel: Theoretical and numerical studies

The multiplicity of smoke flow states may pose a great threat to both human evacuation and emergency rescue in tunnels. A case study is conducted to investigate the multiple steady states of fire smoke transport in a triple-branch tunnel. Both theoretical analysis and numerical simulation are employed in this study. For the case examined in this study, at least three flow regimes are identified under the effects of similar boundary conditions. The results indicate that even for a “well-designed” smoke exhaust system, multiple flow regimes could exist and some flow modes could threaten the human evacuation. The operating point of the mechanical fan system shifts due to the transition between multiple flow regimes. The preliminary results indicate that the inclination angle of the inclined tunnel branches could play an important role in the multiplicity of smoke flow states in such a tunnel system.

Forecasting smoke transport during compartment fires using a data assimilation model

Forecasting simulation of an unknown compartment fire is challenging and usually accompanied with a large number of uncertainties. As the simulation progresses in time, the forecasted physical conditions such as fire heat release rate, room temperature, and vent airflow rate may sway from reality in a highly dynamic environment. Conventional deterministic fire simulation tools using one set of initial inputs to predict fire smoke transport may not easily generate satisfactory results. In this article, a new application of Ensemble Kalman Filter to forecast smoke dispersion during compartment fires is presented. The model utilizes measurement data from multiple sensors in multi-room compartments and is able to predict the fire heat release rate and smoke dispersions within several minutes. In addition, detailed formulation of the Ensemble Kalman Filter model and three case studies are also discussed in this article. The resulting model can be considered as a prototype forecast simulation system to assist occupant evacuation, firefighting, and smoke extraction in a building fire accident.

An Evaluation of Modeled Plume Injection Height with Satellite-Derived Observed Plume Height

Plume injection height influences plume transport characteristics, such as range and potential for dilution. We evaluated plume injection height from a predictive wildland fire smoke transport model over the contiguous United States (U.S.) from 2006 to 2008 using satellite-derived information, including plume top heights from the Multi-angle Imaging SpectroRadiometer (MISR) Plume Height Climatology Project and aerosol vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). While significant geographic variability was found in the comparison between modeled plumes and satellite-detected plumes, modeled plume heights were lower overall. In the eastern U.S., satellite-detected and modeled plume heights were similar (median height 671 and 660 m respectively). Both satellite-derived and modeled plume injection heights were higher in the western U.S. (2345 and 1172 m, respectively). Comparisons of modeled plume injection height to satellite-derived plume height at the fire location (R2 = 0.1) were generally worse than comparisons done downwind of the fire (R2 = 0.22). This suggests that the exact injection height is not as important as placement of the plume in the correct transport layer for transport modeling.

Ventilation effect on fire smoke transport in a townhouse building

AbstractAccidental building fires present considerable valuable information on fire phenomena and behavior. However, fire and smoke movement quantitative data cannot be obtained directly from a building fire accident. Therefore, computational methods have been widely used to reestablish the fire scenario and obtain a great deal of information for fire study. This paper utilized two types of fire simulation software, CFAST and FDS, to reconstruct a motorcycle shop fire accident in Taiwan. Important thermodynamic parameters during the fire duration were obtained through numerical simulations. The impact of natural/forced ventilation on the fire was also studied. The results showed that the more forced airflow into the building, the more time people had to evacuate to a safe place from the fire. © 2006 Wiley Periodicals, Inc. Heat Trans Asian Res, 35(6): 387–401, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/htj.20127

Numerical Investigation of Fire Smoke Transport in the Tsinghua University Sports Center

Fire Dynamics Simulator v3.0 was used to investigate and assess fire smoke transport and management in a realistic indoor sports center. An atrium fire test case illustrated the code's superiority over code-type empirical models for both accuracy and capability. Four fire scenarios in the Tsinghua University Sports Center were then simulated. The smoke layer's descent speed was predicted for each case. The importance of the door effect was revealed and an additional mechanical ventilation system for the building was proved to be of no help. The door effect must be carefully considered in future fire safety designs.