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Incorporating Chemical Activity and Relative Humidity Effects in Regional Air Quality Modeling of Organic Aerosol Formation

Atmospheric particulate matter is known to have significant effects on human health, visibility, and global climate. The magnitudes of these effects, however, depend in complex ways on chemical composition, relative humidity, temperature, phase state, and other parameters. Current regional air quality models such as CMAQ (Community Multiscale Air Quality model) ignore many of these considerations, and consider that the formation of secondary organic aerosol (SOA) can be calculated by assuming thermodynamic ideality in the organic particulate matter (OPM) phase as well as negligible uptake of water into the OPM phase. Theoretical predictions and model simulations considering non-ideality and water uptake show that the standard model assumptions can lead to large errors in predicted SOA mass, and that the magnitude of these errors is sensitive to the composition of the OPM phase.
The SOA module in CMAQ v4.7.1 has been revised in this work to allow consideration of the effects of both non-ideality and water uptake. First, a reasonable specific surrogate structure was assigned to each of the lumped products assumed to be produced by reaction of the different precursor hydrocarbons considered in CMAQ (e.g., isoprene, benzene, and toluene). Second, the CMAQ code was modified to allow iterative calculation (at each point in space and time) of the gas/particle partitioning coefficient for each of the SOA-forming products and for water. Third, model simulations were performed for the Eastern US at a resolution of 36-km x 36-km for late summer 2006, under a range of relative humidity conditions.
When compared with an appropriate base case, the modified code produced increases in SOA ranging from 0.17 to 0.51 micrograms per cubic meter. The average change was 0.30 micrograms per cubic meter, corresponding to a 37% increase in SOA formation. Incorporation of phase separation effects would likely lead to further increases in predicted SOA levels.
Date20 August 2013
CreatorsMarks, Marguerite Colasurdo
Source SetsPortland State University
Detected LanguageEnglish
SourceDissertations and Theses

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