Assessing Forest Canopy Impacts on Smoke Concentrations Using a Coupled Numerical Model

Abstract

The impact of a forest canopy on smoke concentration is assessed by applying a numerical weather prediction model coupled with a Lagrangian particle dispersion model to two low-intensity wildland (prescribed) fires in the New Jersey Pine Barrens. A comparison with observations indicates that the coupled numerical model can reproduce some of the observed variations in surface smoke concentrations and plume heights. Model sensitivity analyses highlight the effect of the forest canopy on simulated meteorological conditions, smoke concentrations, and plume heights. The forest canopy decreases near-surface wind speed, increases buoyancy, and increases turbulent mixing. Sensitivities to the time of day, plant area density profiles, and fire heat fluxes are documented. Analyses of temporal variations in smoke concentrations indicate that the effect of the transition from a daytime to a nocturnal planetary boundary layer is weaker when sensible heat fluxes from the fires are stronger. The results illustrate the challenges in simulating meteorological conditions and smoke concentrations at scales where interactions between the fire, fuels, and atmosphere are critically important. The study demonstrates the potential for predictive tools to be developed and implemented that could help fire and air-quality managers assess local air-quality impacts during low-intensity wildland fires in forested environments.

Decomposing the Interactions between Fire Severity and Canopy Fuel Structure Using Multi-Temporal, Active, and Passive Remote Sensing Approaches

“…Structure also influences the fire environment, or factors affecting the dynamics of the fire, by influencing wind and energy flow through drag [10] and energy absorption [11]. Likewise, models of smoke dispersion through variable canopy architecture allow the prediction of potential smoke dispersion patterns and thus increase knowledge of the degree to which canopy architecture influences forest level air parcel movement [12,13]. As an assemblage of fuel elements, the canopy directly contributes to the dynamics of wildland fires, including rate of spread and energy release [14,15].…”

Fire Behavior, Fuel Consumption, and Turbulence and Energy Exchange during Prescribed Fires in Pitch Pine Forests

“…In some cases, high-intensity fires are preferable for fuel reduction and their ecological benefits but are usually not feasible to conduct in populated areas because of fire-line control and smoke management issues near non-attainment areas for fine particulates, ozone, and other regulated pollutants. Quantitative measures of fuel consumption and above-canopy turbulence and heat fluxes reported here, along with within-canopy and near-surface measurements (e.g., [15,25]), can provide important information for the evaluation of recently-developed physics based fire behavior models targeted at simulating prescribed fires (e.g., QUIC-Fire; [46]), and smoke dispersion models which include the effects of forest canopies on turbulence regimes [14,47,48]. Ultimately, these efforts will assist wildland fire managers design and conduct prescribed fires by employing ignition patterns optimized for desired fire behavior and fuel consumption while simultaneously minimizing impacts to public safety and air quality.…”

“…Computationally intensive, physics based models for simulating fuel combustion and fire behavior (e.g., Wildland Urban Interface Fire Dynamics Simulator (WFDS); [51,52], FIRETEC; [53] and QUIC-Fire; [46]), explicitly account for the processes driving fire behavior by coupling and scaling individual component processes at the fuel bed and fire scales with interactions between ambient wind fields, forest structure, and buoyancy-and shear-induced turbulence on the scale of a fire's plume. Smoke emission and dispersion models (e.g., ARPS-CANOPY/FLEXPART and the BLUESKY modeling framework [14,47,48,54]) couple estimates of fuel consumption and particulate emissions with Lagrangian transport models, and account for characteristics of the forest canopy and how it affects fire-induced turbulence within and above vegetation layers to simulate smoke concentrations during low-and high-intensity fires. A number of model predictions can be evaluated using micrometeorological data collected during fires, but large-scale field experiments such as those reported here have only recently been conducted frequently enough to provide sufficient information to evaluate detailed relationships between ignition pattern and fire behavior, fuel consumption and turbulence and energy fluxes in the fire environment.…”

A Multiscale Numerical Modeling Study of Smoke Dispersion and the Ventilation Index in Southwestern Colorado

“…We wish to make it clear that although we refer to the model by its proper name "FLEXPART-WRF", the model in this study is actually driven by output from the ARPS model. In addition to the previous ARPS-FLEXPART-WRF study in eastern Pennsylvania [8], FLEXPART-WRF has also been coupled to ARPS-CANOPY, a version of ARPS with a canopy parameterization, and used to simulate smoke dispersion during a low-intensity prescribed fire field experiment [39]. In the latter study, the authors concluded from a comparison of smoke plume simulations and field observations that the model was capable of reproducing some of the observed variations in smoke concentrations and plume heights.…”

“…The choice to use FLEXPART-WRF in this study was based mainly on its Lagrangian reference frame, which [40] argue is more suitable for use in complex terrain than Eulerian dispersion models since Lagrangian dispersion models can dynamically compute plume rise and are more computationally efficient at small spatial scales. Also, FLEXPART-WRF has been applied previously to fire and smoke dispersion studies (e.g., [39]), including those in complex terrain (e.g., [41]).…”