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Wildfires, Air Quality, and Modeling


On the morning of December 30, 2021, a wildfire broke out near the town of Marshall, Colorado which is just south of Boulder. Because of exceptionally strong winds (gusting over 100 mph) the fire raced off to the east at an incredible speed, prompting the immediate evacuations of several towns (in some instances people had literally minutes to grab their belongings and flee the oncoming flames). By the next morning the fire had grown to 6200 acres, but thanks to a heavy snowstorm that fell on New Year’s Eve and New Year’s Day, the fire was gone as quickly as it had started.


In terms of size the Marshall Fire was not a big wildfire. But the rapidity with which it spread was certainly impressive, and calls attention to the tremendous danger that wildfires pose. These days that danger is exacerbated both by climate conditions that are increasingly more conducive to wildfires, and the fact that people are building closer and closer to the wildland urban interface—the zone of transition between the wilderness and the land developed by human activity.


Given my profession, as I watched the images and videos of the Marshall Fire that came over the news one of the things I was thinking about was the staggering amount of air pollution that can come from a fire. Now I don’t mean to imply that air pollution is the biggest problem when it comes to wildfires—it most certainly is not—but the pollutants found in wildfire smoke are gigantic in amount and harmful in nature. Fine particulates and gaseous pollution are the pollutants that come most readily to mind, but there also can be numerous hazardous air pollutants (HAPs) in wildfire smoke. A key factor to keep in mind is when there’s a big wildfire there’s a lot more than trees that burn—for those huge fires that burn millions of acres and destroy towns it’s important to remember that everything burns. So the glues that are in flooring in buildings—they burn and release HAPs. The cars that are full of gasoline—they burn and release HAPs. Of course, air quality impacts from wildfires are generally short-lived (hopefully just a matter of days), but if you ever find yourself being impacted by wildfire smoke you would be wise to take actions to protect yourself as that kind of air quality can be truly horrendous.


From a modeling standpoint (after all, I am a modeler!) the modeling of wildfires is very different than the modeling that BSM typically does for its industrial clients. A stack venting emissions from a combustion source is far more straightforward to model than a wildfire. Below is a quick comparison of some modeling parameters and how they stack up (ahem) in both “traditional” modeling and wildfire modeling.

Parameter

Point Source ("Smokestack")

Wildfire

Location

Fixed

Varies with time, influenced by topography, meteorology, and land use

Emissions

Usually one fuel, sometimes a backup fuel

Many different "fuels." Different grasses/trees emit different pollutants when burned; each town has different things that can burn, meaning different pollutants come from each town

Source characteristics

Diameter is fixed; velocity and temperature can be bounded pretty easily

Dimensions/orientation are constantly changing; velocities and temperature can vary wildly over both time and space depending on many factors

Last summer BSM participated in a Department of Homeland Security project on improving the lead-time for wildfire detection through the use of early wildfire detection sensors (scroll about halfway down in this June 2021 press release from the White House to read more: https://www.whitehouse.gov/briefing-room/statements-releases/2021/06/30/fact-sheet-the-biden-harris-administration-acts-to-address-the-growing-wildfire-threat/). The modeling we did as part of that project was a very different kind of modeling from the wildfire modeling described above…along those lines stay tuned, because we hope to share with you in the near future some of the exciting things we have in the works that will greatly improve wildfire detection/response!

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