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`Sensitivity of Aermod in modeling fugitive dust emissions sources,` presented at guideline on air quality models: next generation of models conference 2009

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Dispersion modelers have long faced challenges estimating ambient pollutant concentrationscaused by releases from “fugitive” sources of particulate matter, such as paved and unpavedroadways, raw material storage piles, outdoor material processing operations, agriculturalactivities, or windblown dust in general. Fugitive emissions are commonly defined as those thatcould not reasonably pass through a stack, chimney, vent, or other functionally equivalentopening. Aside from their non-point release characteristics, the unsteady state nature of mostfugitive emitting activities is what makes them particularly problematic when simulated bysteady-state dispersion models. Further, there has been limited field testing completed to provideperformance evaluations that would support the models for these types of releases.

The primary regulatory guidance from the Environmental Protection Agency for modelingfugitive emissions is given in the Guideline on Air Quality Models (40 CFR 51, Appendix W).1Section of the Guideline, specific to PM10 modeling, refers the user to Section 4.2.2 “forsource-specific analyses of complicated sources”, but that section says little concerning fugitivesources. In the AERMOD user’s manual2, methodologies are offered for modeling fugitivesources. Many state air regulatory agencies have also prescribed specific protocols for modelingfugitive PM sources.

However, application of many of the general and/or prescribed techniquescan yield unrealistically high air concentrations relative to the nature and magnitude ofemissions, particularly when receptors are located close to fugitive sources.This paper explores common presumptions about fugitive source modeling techniques byexamining the sensitivity of predicted PM ambient concentrations to the choice of model(AERMOD versus ISCST3), changes in source representation (volume versus area source), andvariations in chosen source dimensions. The affect of key meteorological data parameters, suchas wind speed and land use, are also reviewed.

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