How Does Controlled Burning Lessen the Effects of Wildfires?

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Large wildfires destroy vast amounts of nature and property and negatively impact public health and the environment. Climate change and other factors have increased the frequency and severity of wildfires in recent years, so forest management planners are implementing new or modified fire prevention and management practices to mitigate the effects of future wildfires, which is a shift from historical practices that almost entirely focused on suppressing fires after they started. Controlled burning, where forest managers deliberately introduce small fires to reduce the amount of fuel available to a future wildfire, is becoming an increasingly common practice. But from a public health perspective, there is a question of “How much controlled burning is too much?”. Recent research found a “goldilocks” approach whereby a moderate amount of controlled burning can strike a balance between reducing the size, severity, and duration of large wildfires while not creating a public health burden from exposure to too much smoke is an advisable path forward.

The US Wildfire Problem in Numbers and Context

Anyone who has experienced the effects of wildfires knows their effects can range from devastating (complete loss of your home, your town, your region) to inconvenient (hazy conditions, having to stay inside during periods of smoke). The scientific literature generally finds all sorts of associations between smoke exposure and a series of respiratory issues (e.g., making asthma worse, causing temporary hospitalizations, and even death).

What are the various causes of wildfires? Let’s turn to the US Forest Service, which has 13 unique fire cause codes:

What are the biggest causes of wildfires among these 13 possibilities? The answer is a little murky. You may be surprised to know there’s enormous disagreement among multiple US federal services who have some role in understanding, tracking, measuring, and reporting on the seemingly fundamental question of “how many fires get started and what was the cause?”. Want to see a crazy - but seemingly representative example? Look at this figure below, taken from a US Forest Service paper:

Some government agencies suggest that more than 80% of all wildfires are caused by humans in some way - again, as we can see, there is wild disagreement even in how many fires occur, so I’m not sure how much we can take that 80% estimate to the bank. But there does seem to be general agreement that, for the most part, humans do cause most wildfires, which probably led to the investment and creation of this guy:

How big is the wildfire issue in the US? Data from the National Centers for Environmental Information tell us that, on average, around 70,000 fires occur annually nationally, burning 7 million acres of land. The figure below shows recent data from 2012 through 2022.

If you’re not used to thinking in acres, let’s put that 7 million acres burned annually in context. One of my favorite bits of trivia is that Jacksonville, Florida is the largest city by land area in the US at about 560,000 acres. So every year, about 13 Jacksonvilles are burned in the US from wildfire.

As a final point, going beyond the dimensions of estimated damage caused by wildfires, let’s look at the economic losses linked to wildfires. A recent estimate by a US congressional committee called JEC put the annual financial loss from wildfires at $894 billion, and the figure below represents the estimated annual cost across nine main categories. This figure is at the upper end of their estimated range. The absolute magnitude of economic loss should probably be taken with some grains of salt - as we established earlier, there’s wide disagreement in the most basic measures of wildfires, so we’d also expect financial loss estimates to have a similarly large range. Regardless of the specific magnitude, the physical and economic damage from wildfires is pretty substantial.

3 Main Methods to Reduce the Frequency and Severity of Wildfires

Active forest management seeks to reduce the frequency and severity of wildfires. Three methods are mainly used to accomplish this: Hand Thinning, Mechanical Thinning, and Controlled Burning.

Hand Thinning

Hand thinning is mainly done to remove smaller-diameter trees. These smaller trees are considered “ladder fuels,” meaning they can enable fires burning closer to the ground to migrate upward.

Mechanical Thinning

Mechanical thinning goes harder than hand thinning, employing equipment like large cranes, bulldozers, wood chippers, and the (incredibly named!) feller buncher which literally translates to “cut down tree then gather it.”

Controlled Burning

Controlled burning is a process intended to mirror naturally-occurring fires, and the process to plan and implement a controlled burn is fairly involved (here for your reading pleasure is a 115-page controlled burning manual). Did you know one of the jobs involved in carrying out a controlled burn is called a Prescribed Fire Burn Boss?

Each of the three types of interventions has its part in reducing the severity of major wildfires and is often used in tandem (e.g., thinning may be carried out before starting a controlled burn campaign).

New Study: How Much Controlled Burning is Too Much?

Now that we have established how frequently wildfires occur, tallied up the physical and economic damage they can wreak, and reviewed interventions used to reduce the frequency and severity of wildfires, let’s turn our focus to a new study that asks a question that I’ll sum up as follows: “Wildfires cause lots of physical damage, economic damage, and harm to public health. Controlled burns can reduce the severity of wildfires, but this type of burning also creates smoke emissions, which harms public health. Is there a balancing point where we can effectively reduce the occurrence and damage from wildfires using controlled burns but not doing so much controlled burning that we create a new public health problem from smoke emissions?”

This type of study falls into a particular archetype common in the sciences that I’ll call “Model Development and Application with a Case Study.” There’s a quote attributed to statistician George Box that “All models are wrong; some are useful.” I tend to agree, but the fact that models that scientists use to understand the world are generally wrong does not mean they lack value. Anyone who has taken high school chemistry knows the ideal gas law that describes the relationship between pressure, volume, and temperature for a gas (PV = nRT). It turns out that this model is wrong, and there are several edge cases and other factors not accounted for in this equation - but it gets you pretty close to reality and is relatively easy to use. So it’s a helpful model.

Lots of researchers develop new models in their work as a way of making sense of complex phenomena. Models may manifest as various analytical or numerical equations or simple (or complex) computer models that link relationships across scientific domains. We’ve previously talked about life-cycle analysis as a helpful modeling framework to account for the emissions and environmental impacts of a product or process across its life cycle. Once a scientific model is developed, researchers will commonly apply it to a real-world case study to demonstrate its usefulness (and perhaps accuracy, robustness, etc.)

In this new study, the researchers highlight a historical disconnect between forest managers (who are charged with implementing preventive measures to avoid wildfires and work with coordinated teams to address wildfires when they occur) and public health officials (who are charged with monitoring and implementing guidance to protect public health including during natural disasters like wildfires). Namely, that controlled burning is a commonly-used intervention to prevent or reduce impacts from wildfires, but the effects of controlled burning are underexplored. So the researchers built a new model to bridge this gap and understand how varying the amount of controlled burning reduced wildfires, but then, consequently, how much the additional smoke from controlled burning could affect public health. They then apply their model to a fire-prone area in the Tahoe-Central Sierra Initiative region in California and test its accuracy and results against nearly 20 years of historical data.

What’s clever about this new study is how it incorporates multiple scientific disciplines, techniques, and data sets to make sense of their study region toward answering their central research question. Here’s how they did it:

• Generate Forest Management Scenarios. They worked with forest managers to create realistic scenarios of more and more aggressive wildfire prevention techniques, including a “do nothing” case, a “business as usual” (BAU) case with mostly hand and mechanical thinning, and then four scenarios of more and more controlled burning.

• Model the smoke emissions that occur. For each scenario, the researchers estimated the amount of smoke that would happen.

• Model how much nearby populations are exposed to smoke, based on the smoke emission estimates and modeling atmospheric conditions.

• Model the direct public health effects occurring based on the amount and duration of smoke exposure, along with population demographics.

So what did they find? First, as you might expect, the amount of smoke created is worst in the “do nothing” scenario, which they called Minimal Management, followed by the BAU case. The four controlled burn scenarios resulted in far fewer smoke emissions compared to the minimal management and BAU scenarios. The values in each panel shown below give a nice depiction of how concentrated the smoke gets in the modeled area and how far that smoke emanates.

The authors also found in their model that the scenarios with controlled burning tended to reduce the amount of time that wildfire season would last, on the order of about a month’s difference.

To understand the potential public health impacts from the six forest management scenarios described earlier, the researchers examined outcomes in terms of (i) asthma-related hospitalizations and (ii) emergency room (which they called emergency department) visits caused by increased amounts of smoke exposure in the nearby population. Let’s take a look at the hospitalization modeling results:

We can see in the above figure that although the four controlled burning scenarios all resulted in a decrease in modeled asthma-related hospitalizations, the magnitude of the difference is pretty small (maybe a difference of around 5 or 10 hospitalizations per year in the study area in California). Still, there’s a notable difference in the “Fire” scenario versus the more aggressive controlled burn scenarios (Fire+ and Fire++), suggesting that a modest amount of controlled burning reflects a “goldilocks” scenario that balances wildfire smoke reduction, wildfire season duration, and public health impacts.

That the magnitude between each scenario is relatively small underscores an important point: more aggressive controlled burning (which takes additional time, financial resources, more fire management personnel, etc) gives diminishing returns from a public health impact, which is an important finding from this work. More broadly, the integrated model developed by the researchers can be generalized and applied to other fire-prone regions of the US, provided the various multidisciplinary data are available at similar levels of accuracy and granularity.

Insights and Implications

Here are some insights and implications of this new study that come to mind:

1. Most corporate sustainability teams that publish their sustainability goals and progress often incorporate so-called physical climate risk models into their planning and reporting, where the effects of things like wildfires and other natural disasters are evaluated, and the company indicates how they plan to address risks from these events to their operations and supply chains. New, integrated models like that discussed here represent an evolution that may bring into sharper focus the magnitude of physical risks from wildfire based on planned wildfire management practices, which, in theory, should improve decision-making processes by corporations when planning risk mitigation measures.

2. The authors’ main goal was to develop and display a new integrated model that could inform public health effects stemming from various realistic wildfire mitigation scenarios and practices. Health officials have already guided the public in minimizing the impacts of wildfire smoke after it happens. Still, with this new work, there is a new tool where public health officials can be brought into the wildfire and smoke prevention process alongside forest managers and explicitly link various wildfire mitigation measures to health outcomes. Naturally, an improved planning process informed by data should result in better health outcomes for the public living near wildfire-prone areas.

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