Source Apportionment

Most air monitoring programs are designed to measure particulate mass loading to provide data for PM10 and PM2.5 NAAQS and visibility. Because these sizes of particles can come from many sources, they are not useful for apportioning to one source or another. While the Interagency Monitoring of Protected Visual Environments (IMPROVE) program provides speciated aerosol data that are helpful in source attribution analysis, the averaging periods of samples and sparse location of sites make IMPROVE measurements difficult to use for source attribution without supplemental measurements or modeling tools.

Wotawa and Trainer (2000) found that 74 percent of the variance in the average afternoon carbon monoxide levels could not be attributed to anthropogenic sources during the 1995 Southern Oxidant Study (Chameides and Cowling 1995). Analysis of weather patterns indicated that transport of wildland fire smoke from Canada could explain the elevated carbon monoxide levels. Also, they discovered a statistically significant relationship between the elevated carbon monoxide and ground-level ozone concentrations.

Characterization of organic carbon compounds found within the organic carbon fraction of fine particulate matter coupled with inclusion of gaseous volatile organic compounds (VOCs) holds substantial promise in advancing the science of source apportionment (Watson 1997). The key to the use of chemical mass balance methods is the acquisition of accurate data describing the chemical composition of both particulate matter and VOCs in the ambient air and in emissions from specific sources. Several organic compounds unique to wood smoke have been identified including retene, levoglucosan, thermally altered resin, and polycyclic aromatic hydrocarbons (PAH) compounds. These compounds are present in appreciable amounts and can be used as signatures for source apportionment if special precautions are taken during sampling to minimize losses (Standley and Simoneit 1987). Inclusion of these aerosol and VOC components in the speciation analysis appears worthwhile but would increase monitoring and sample analysis costs.

Source Apportionment Methods

Apportionment of particulate matter mass to the respective contributing sources is done through both mechanistic models (dispersion models) and receptor-oriented techniques that are based on the characteristics of the particles collected at the receptor. The best approach is through the use of both techniques, applied independently, to develop a "weight of evidence" assessment of source contributions of smoke from fire. A third approach is through the use of visual and photographic systems that can document visibility conditions over time or track a plume from its source to the point of impact within a Class I area.

Receptor-Oriented Approaches

Receptor-oriented approaches range from simple signature applications to complex data analysis techniques that are based on the spatial, temporal, and chemical constituents ("fingerprint") of various sources.

Simple signature applications for smoke from fire are based on chemically distinct emissions from fire. For example, methyl chloride (CH3Cl) is a gas emitted during wood combustion that has been used in this manner to identify impacts of both residential woodstove smoke and smoke from prescribed fires (Khalil and others 1983).

• Speciated Rollback Model: a simple hybrid model that uses aerosol data collected at the receptor with emission inventories to estimate source impacts.
• Chemical Mass Balance Model CMB7: infers source contributions based on speciated aerosol samples collected at a monitoring site.

Receptor-oriented methods of particle mass source apportionment have proven successful in a large number of urban studies worldwide. A number of these studies have attempted to apportion wildfire smoke on the basis of a set of aerosol and source emission trace elements and compounds. The experimental design of these studies has limited the ability of receptor models to resolve wildfire smoke from other sources. With improvements in speciation of the organic carbon component of the aerosol, and inclusion of carbon monoxide, methyl chloride, and other endemic signatures, the ability of these techniques to resolve sources and minimize uncertainties will increase. Sensitivity studies are needed to determine which additional components beyond the standard array of trace elements, ions, and carbon fractions would be most beneficial to include in future monitoring programs.

Mechanistic Models

Multiple dispersion models have been used to estimate air quality impacts of single or multiple fires at local and regional scales. Eulerian regional-scale models have been principally used for source apportionment application both to estimate contributions to particulate air quality and regional haze. The suitability of such models for apportionment applications largely depends on the completeness and accuracy of the emission inventory inputs used by the model. Unfortunately, few field validations are available.