Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn

California Case Study of Wildfires and Prescribed Burns: PM2.5 Emissions, Concentrations, and Implications for Human Health

Wildfires are a significant threat to human health, in part through degraded air quality. Prescribed burning can reduce wildfire severity but can also lead to an increase in air pollution. The complexities of fires and atmospheric processes lead to uncertainties when predicting the air quality impacts of fire and make it difficult to fully assess the costs and benefits of an expansion of prescribed fire. By modeling differences in emissions, surface conditions, and meteorology between wildfire and prescribed burns, we present a novel comparison of the air quality impacts of these fire types under specific scenarios. One wildfire and two prescribed burn scenarios were considered, with one prescribed burn scenario optimized for potential smoke exposure. We found that PM2.5 emissions were reduced by 52%, from 0.27 to 0.14 Tg, when fires burned under prescribed burn conditions, considerably reducing PM2.5 concentrations. Excess short-term mortality from PM2.5 exposure was 40 deaths for fires under wildfire conditions and 39 and 15 deaths for fires under the default and optimized prescribed burn scenarios, respectively. Our findings suggest prescribed burns, particularly when planned during conditions that minimize smoke exposure, could be a net benefit for the impacts of wildfires on air quality and health.

The Impact of Post-Fire Smoke on Plant Communities: A Global Approach

Smoke is one of the fire-related cues that can alter vegetation communities' compositions, by promoting or excluding different plant species. For over 30 years, smoke-derived compounds have been a hot topic in plant and crop physiology. Research in this field was initiated in fire-prone areas in Australia, South Africa and some countries of both Americas, mostly with Mediterranean-type climates. Then, research extended to regions with moderate climates, like Central European countries; this was sometimes determined by the fact that in those regions, extensive prescribed or illegal burning (swailing) occurs. Hence, this review updates information about the effects of smoke compounds on plant kingdoms in different regions. It also focuses on research advances in the field of the physiological effects of smoke chemicals, mostly karrikins, and attempts to gather and summarize the current state of research and opinions on the roles of such compounds in plants' lives. We finish our review by discussing major research gaps, which include issues such as why plants that occur in non-fire-prone areas respond to smoke chemicals. Have recent climate change and human activities increased the risk of wildfires, and how may these affect local plant communities through physiologically active smoke compounds? Is the response of seeds to smoke and smoke compounds an evolutionarily driven trait that allows plants to adapt to the environment? What can we learn by examining post-fire smoke on a large scale?

Modeling Low Intensity Fires: Lessons Learned from 2012 RxCADRE

Coupled fire-atmosphere models are increasingly being used to study low-intensity fires, such as those that are used in prescribed fire applications. Thus, the need arises to evaluate these models for their ability to accurately represent fire spread in marginal burning conditions. In this study, wind and fuel data collected during the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiments (RxCADRE) fire campaign were used to generate initial and boundary conditions for coupled fire-atmosphere simulations. We present a novel method to obtain fuels representation at the model grid scale using a combination of imagery, machine learning, and field sampling. Several methods to generate wind input conditions for the model from eight different anemometer measurements are explored. We find a strong sensitivity of fire outcomes to wind inputs. This result highlights the critical need to include variable wind fields as inputs in modeling marginal fire conditions. This work highlights the complexities of comparing physics-based model results against observations, which are more acute in marginal burning conditions, where stronger sensitivities to local variability in wind and fuels drive fire outcomes.

Performance Evaluation of an Operational Rapid Response Fire Spread Forecasting System in the Southeast Mediterranean (Greece)

The current work presents the operational implementation and evaluation of a rapid response fire spread forecasting system, named IRIS, that was developed to provide support to the tactical wildfire suppression activities of the Hellenic Fire Corps. The system was operationally employed during the 2019 fire season in Greece, providing on-demand wildfire spread predictions for 17 incidents. Satellite remote sensing data were employed for quantitatively assessing IRIS’s predictions for eight selected events. Our results suggest an overall satisfactory model performance. More importantly, this study demonstrates that, as coupled fire-atmosphere modeling becomes an increasingly popular approach, the respective models have great potential to support operational agencies and wildfire managers during the incident phase.