Modeling semivolatile organic aerosol mass emissions from combustion systems

Manish K. Shrivastava, Eric M. Lipsky, Charles O. Stanier, Allen L. Robinson

Research output: Contribution to journalArticlepeer-review

121 Scopus citations


Experimental measurements of gas-particle partitioning and organic aerosol mass in diluted diesel and wood combustion exhaust are interpreted using a two-component absorptive-partitioning model. The model parameters are determined by fitting the experimental data. The changes in partitioning with dilution of both wood smoke and diesel exhaust can be described by two lumped compounds in roughly equal abundance with effective saturation concentrations of ∼1600 μg m-3 and ∼20 μg m-3. The model is used to investigate gas-particle partitioning of emissions across a wide range of atmospheric conditions. Under the highly dilute conditions found in the atmosphere, the partitioning of the emissions is strongly influenced by the ambient temperature and the background organic aerosol concentration. The model predicts large changes in primary organic aerosol mass with varying atmospheric conditions, indicating that it is not possible to specify a single value forthe organic aerosol emissions. Since atmospheric conditions vary in both space and time, air quality models need to treat primary organic aerosol emissions as semivolatile. Dilution samplers provide useful information about organic aerosol emissions; however, the measurements can be biased relative to atmospheric conditions and constraining predictions of absorptive-partitioning models requires emissions data across the entire range of atmospherically relevant concentrations.

Original languageEnglish (US)
Pages (from-to)2671-2677
Number of pages7
JournalEnvironmental Science and Technology
Issue number8
StatePublished - May 15 2006

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • Environmental Chemistry


Dive into the research topics of 'Modeling semivolatile organic aerosol mass emissions from combustion systems'. Together they form a unique fingerprint.

Cite this