Prescribed fire (RxB) is an effective management tool often used by installation natural resource managers to achieve the goals of fuel reduction, ecological restoration, invasive species control, and others. However, despite the positive benefits of RxB, it does not come without tradeoffs. One of the costs of RxB operations is the generation of smoke, a respiratory hazard that impacts firefighter health and safety and potentially that of local downwind communities if smoke is not adequately managed. Similarly, smoke can impact installation training operations and other activities due to the visual hazard it presents. Next generation fire behavior models are improved predictive tools that have been developed to help managers enhance their fire and smoke management tactics to mitigate tradeoffs of prescribed burning while maximizing the desired outcomes. A missing gap in the testing and refinement of these models involves the conditions that drive near-field smoke emissions, that is near the flaming and smoldering combustion. To resolve this gap, new information gathered at the near-field source is needed to fine-tune model algorithms. This contrasts with information collected further away from the flaming front where atmospheric mixing and photolysis (molecular separation by light) have changed the chemical and physical composition of the smoke. Building on the successes and lessons of RC-2641, the project team plans to create a suite of systematic and controlled experiments that will be conducted at the laboratory and field scales to study the coupling between fire behavior and emissions for different fuel and environmental conditions. These will improve the understanding of, and ability to accurately predict, fire behavior under a wide range of management scenarios.

The specific objectives of this project will be to:

1. Estimate emissions from fire behavior, fuel, and environmental parameters.
2. Link the fire behavior in the near-field to emissions across different scales.
3. Develop source terms for implementation in wildland fire and smoke modelling tools.

To further the understanding of near-field emissions and improve its modeling, a multi-scale approach will be adopted. This approach will allow for systematic and accurate emission measurements at the laboratory scale before extending it to field and operational scale burns (prescribed burns). Laboratory scale experiments (flammability test, two-dimensional and three-dimensional flame spread) conducted at Worchester Polytechnic Institute will investigate the fundamental coupling between fuel structure, fire characteristics and emissions (in terms of emission factors). The fire spread and its link to near-field emissions at field scale will be studied at the Silas Little Experimental Forest. Instrumentation of prescribed burns (~50 – 100 burns) across the U.S. will extend the availability of emissions data for several external conditions and fuel categories. The database generated through the experiments will be used to derive the source terms and emission factors to be used in physics-based fire and smoke modeling tools such as FIRETEC, ensuring complementarity with the new SERDP project, RC24-4294, and bridging the gap between combustion and downstream emissions. This will ensure the fidelity of the model to predict emissions for a wide variety of fuel and external conditions.

The emissions database developed through this project will serve as a direct near-field emission survey of different ecosystems and conditions. This will provide managers and model developers with a deepened understanding of the compounds (gases and particles) emitted at the level of the fire front and support the refinement of predictions of emissions from prescribed burns. In addition, this database will provide the specific source terms of emission required for next generation computational fluid dynamics-based models, particularly FIRETEC. In addition to FIRETEC, most of the models that include long-range emissions are based on strong assumptions due to the lack of detailed or accurate source term availability and this project will fill that gap.