Transport, Dispersion, and Modeling of Fire Emissions

To anticipate the impacts of smoke, the timing and location of smoke concentrations become important. Data on the site-specific surface concentrations of respirable particles and gases often are needed for estimating impacts on public health and welfare. Data on the cumulative concentrations of elements that scatter and absorb light also are needed to estimate impacts on visibility and haze. Ambient air quality can be measured at a point or as distribution of air quality over any space and time of interest. Ambient air quality is affected by:

• the pollutants emitted to the atmosphere from fires,
• the background air quality that has already been degraded by other sources,
• the transport of the polluted parcels of the atmosphere,
• dispersion due to atmospheric movement and turbulence, secondary reactions, and removal processes.

Plume rise is an important component of transport, because it determines where in the vertical structure of the atmosphere dispersion will begin. Other basic elements that are important in the trajectory and dispersion of smoke are heat release, advection and diffusion, scavenging, and chemical transformations.

Overall, transport and dispersion has proven extremely difficult to model accurately, especially in complex terrain. For example, detailed, gridded, three-dimensional meteorological data are required to model transport and dispersion, but expert judgment is often required to supplement or substitute for such modeled predictions. Despite the difficulties of modeling, since about 1990 modeling systems used to assess the air quality impact of fires have grown increasingly important to both the fire planning and air quality communities. Today, there is a broad range of transport and dispersion models available. These models fall into four major categories:

• Plume models (VSMOKE and SASEM)
• Puff models (Hysplit, Calpuff, and NFSpuff)
• Particle models (PB-Piedmont)
• Grid models(REMSAD, Models-3/ CMAQ)

Although progress has been made, none of the currently available models fully meet the needs of fire planners and air resource managers. Much of the deficiency in current modeling approaches is caused by inherent uncertainties associated with turbulent motions between the fire, smoke, and the atmosphere that are compounded by the highly variable distribution of fuel elements, composition, and condition. Another source of deficiency is that most available models were originally designed for well-behaved sources such as industrial stacks or automobile emissions, while emissions from fire can be extremely variable in both time and space. Also, outputs from currently available models do not always match the temporal or spatial scale needed for land management application.

Due to these deficiencies, current models to predict trajectory or air quality impacts from fires are inadequate in coverage and are incomplete in scope (Sandberg and others 1999). Application of these models are appropriate mainly for relatively homogeneous fuelbeds and steady state burn conditions, restricting them to fires on a local scale or to those where fuels are scattered or piled uniformly over the landscape.

Because of new interest in modeling emissions on a regional scale, land managers need transport and dispersion models that include all fire and fuel types as well as multiple sources. Such models need to be linked to other systems that track fire activity and behavior as well as provide for variable scaling to fit the area of interest. At the operational level, models that support real-time decision making during fire operations in both wildland fire situation analysis and go/no-go decision making are also needed (Breyfogle and Ferguson 1996).