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Published May 15, 2002 | Supplemental Material
Journal Article Open

Evaluation of an Air Quality Model for the Size and Composition of Source-Oriented Particle Classes

Abstract

Air quality model predictions of the size and composition of atmospheric particle classes are evaluated by comparison with aerosol time-of-flight mass spectrometry (ATOFMS) measurements of single-particle size and composition at Long Beach and Riverside, CA, during September 1996. The air quality model tracks the physical diameter, chemical composition, and atmospheric concentration of thousands of representative particles from different emissions classes as they are transported from sources to receptors while undergoing atmospheric chemical reactions. In the model, each representative particle interacts with a common gas phase but otherwise evolves separately from all other particles. The model calculations yield an aerosol population, in which particles of a given size may exhibit different chemical compositions. ATOFMS data are adjusted according to the known particle detection efficiencies of the ATOFMS instruments, and model predictions are modified to simulate the chemical sensitivities and compositional detection limits of the ATOFMS instruments. This permits a direct, semiquantitative comparison between the air quality model predictions and the single-particle ATOFMS measurements to be made. The air quality model accurately predicts the fraction of atmospheric particles containing sodium, ammonium, nitrate, carbon, and mineral dust, across all particle sizes measured by ATOFMS at the Long Beach site, and in the coarse particle size range (D_a ≥ 1.8 μm) at the Riverside site. Given that this model evaluation is very likely the most stringent test of any aerosol air quality model to date, the model predictions show impressive agreement with the single-particle ATOFMS measurements.

Additional Information

© 2002 American Chemical Society. Received for review September 5, 2001. Revised manuscript received February 11, 2002. Accepted February 11, 2002. This research was supported by the U.S. Environmental Protection Agency under agreement No. R826371-01-0. Thanks are due to Don-Yuan Liu and Keith Coffee from the University of California at Riverside and Philip Silva from Aerodyne Research, Inc., for their assistance with this work.

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