Issue 7

Air Quality Issues Lead to a New Understanding of Day Smoke

The particulate matter and ozone derivatives produced by both wildfires and prescribed burning have an undeniable effect on air quality. In 1998, the U.S. Environmental Protection Agency (EPA) issued an interim policy to protect public health from the impacts of air pollutants from wildland fires. As part of this policy, the EPA urged the States to develop smoke management programs. Land managers accustomed to planning for smoke hazards needed new tools to look at less visible air quality effects from prescribed fires.

With funding from the 2001 National Fire Plan and the computing power of the Southern High-Resolution Modeling Consortium (SHRMC), the SRS Smoke Management Team of Gary Achtemeier, Scott Goodrick, and Yongqiang Liu began developing a research tool, the Southern Smoke Simulation System (SHRMC–4S) to model fire emissions, smoke movement, and air quality effects.

SHRMC–4S integrates the Community Multiscale Air Quality model developed by the EPA with the high-resolution weather prediction data generated by SHRMC with Daysmoke, a program SRS researchers developed to simulate the behavior of smoke plumes from prescribed burning—and to correct assumptions in the prevailing models that might have led to restrictions on an important forest management practice.

“When we started working with the air quality community, we found out that the system being used averaged burns over an entire year, when there are really only 30 days or so in the year that managers can burn on,” says Achtemeier. “This greatly exaggerated the air quality effects from prescribed burning. We developed Daysmoke to indicate the exact day and time of burns, and to take into account how managers engineer their burns so that smoke sweeps up and away.”

And then there is the structure of wildland smoke. EPA particulate models are based on simple smokestack plumes. A prescribed fire incident in spring 2006 caused SRS researchers to change how they look at the structure of smoke from wildland fires—and may change the way particulate concentrations in air are modeled in the future.

In April 2006, smoke from a prescribed burn in Cocke County, TN, jumped over the mountains to find its way into the streets of Asheville, NC. When Achtemeier plugged data from the burn into Daysmoke, the model predicted only a tenth of the particulate concentrations recorded in Asheville. Puzzled, he went to satellite images and ground-level photo images of the event and noticed that what looked like one big plume of smoke on the satellite images was actually made up of many small updraft cores. When he simulated five or six cores in Daysmoke, the model gave a more accurate reading.

“This discovery gave us more answers about why other models were not predicting air quality effects from prescribed burning more accurately,” says Achtemeier. “Our next step is to develop an umbrella code that brings all these findings together. When we have that, we’ll run a simulation using data from Florida to see how close we are getting to accurately predicting air quality effects.”

For Achtemeier, Goodrick, and Liu, even the sky may not be the limit. In the planning stage are products that link short-term and long-term climate data with wildfire, prescribed fire, and smoke management data to look at the effects of climate on wildland fire—as well as the effects of fire in the Southeast on climate.

For more information:

Gary Achtemeier at 706-559-4239 or gachtemeier@fs.fed.us

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