Researcher aims to combat wildfires with Chemical Engineering

This summer Southern Ontario residents experienced the decreasingly rare occurrence of smoke from wildfires adversely affecting the air quality. The climate emergency is ramping up and wildfires are an inevitable outcome. This year’s wildfire season started early and has already burned an unprecedented area of Canadian forests, destroying homes and businesses in its unrelenting path.

Wildfires are difficult to predict. Firefighters often use treatments such as prescribed burns or controlled burns in which firefighters preemptively burn a small piece of forest to manage wildfire risk and attempt to reduce the hazards associated with fires. Firefighters require accurate predictions of a fire’s trajectories, weather patterns, smoke composition and many other factors to make crucial decisions in preventing and combating wildfires.

A new Chemical Engineering faculty member, Professor Joshua Pulsipher is applying his expertise in Computational Chemical Engineering to identify more effective ways to prevent and mitigate wildfires. Pulsipher uses state-of-the-art simulation models to predict and advanced optimization methods to control wildfire risk. He utilizes the chemical engineering concept of transport phenomena in his analysis. This is important, as within wildfires there are chemical reactions and chemical diffusion together.

Two different models are critical for predicting wildfire behaviour. The first is the wildfire combustion model, which typically relies on complex multi-scale reaction and diffusion phenomena that are highly random and rely on several other factors such as foliage conditions. There is also a climate and weather model which describes local weather patterns such as wind and humidity that significantly influence wildfires. These models are highly interconnected as wildfires and weather affect each other. However, the current practice is to use these separately because they both are highly resource and time-intensive to run.