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Volume 15, issue 21
Atmos. Chem. Phys., 15, 12283-12313, 2015
https://doi.org/10.5194/acp-15-12283-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Carbonaceous Aerosols and Radiative Effects Study (CARES)

Atmos. Chem. Phys., 15, 12283-12313, 2015
https://doi.org/10.5194/acp-15-12283-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Nov 2015

Research article | 06 Nov 2015

Modeling particle nucleation and growth over northern California during the 2010 CARES campaign

A. Lupascu1, R. Easter1, R. Zaveri1, M. Shrivastava1, M. Pekour1, J. Tomlinson1, Q. Yang1, H. Matsui2,3, A. Hodzic4, Q. Zhang5, and J. D. Fast1 A. Lupascu et al.
  • 1Pacific Northwest National Laboratory, Richland, Washington, USA
  • 2Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
  • 3Department of Environmental Geochemical Cycle Research, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
  • 4National Center for Atmospheric Research, Boulder, Colorado, USA
  • 5Department of Environmental Toxicology, University of California, Davis, California, USA

Abstract. Accurate representation of the aerosol lifecycle requires adequate modeling of the particle number concentration and size distribution in addition to their mass, which is often the focus of aerosol modeling studies. This paper compares particle number concentrations and size distributions as predicted by three empirical nucleation parameterizations in the Weather Research and Forecast coupled with chemistry (WRF-Chem) regional model using 20 discrete size bins ranging from 1 nm to 10 μm. Two of the parameterizations are based on H2SO4, while one is based on both H2SO4 and organic vapors. Budget diagnostic terms for transport, dry deposition, emissions, condensational growth, nucleation, and coagulation of aerosol particles have been added to the model and are used to analyze the differences in how the new particle formation parameterizations influence the evolving aerosol size distribution. The simulations are evaluated using measurements collected at surface sites and from a research aircraft during the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted in the vicinity of Sacramento, California.

While all three parameterizations captured the temporal variation of the size distribution during observed nucleation events as well as the spatial variability in aerosol number, all overestimated by up to a factor of 2.5 the total particle number concentration for particle diameters greater than 10 nm. Using the budget diagnostic terms, we demonstrate that the combined H2SO4 and low-volatility organic vapor parameterization leads to a different diurnal variability of new particle formation and growth to larger sizes compared to the parameterizations based on only H2SO4. At the CARES urban ground site, peak nucleation rates are predicted to occur around 12:00 Pacific (local) standard time (PST) for the H2SO4 parameterizations, whereas the highest rates were predicted at 08:00 and 16:00 PST when low-volatility organic gases are included in the parameterization. This can be explained by higher anthropogenic emissions of organic vapors at these times as well as lower boundary-layer heights that reduce vertical mixing. The higher nucleation rates in the H2SO4-organic parameterization at these times were largely offset by losses due to coagulation. Despite the different budget terms for ultrafine particles, the 10–40 nm diameter particle number concentrations from all three parameterizations increased from 10:00 to 14:00 PST and then decreased later in the afternoon, consistent with changes in the observed size and number distribution. We found that newly formed particles could explain up to 20–30 % of predicted cloud condensation nuclei at 0.5 % supersaturation, depending on location and the specific nucleation parameterization. A sensitivity simulation using 12 discrete size bins ranging from 1 nm to 10 μm diameter gave a reasonable estimate of particle number and size distribution compared to the 20 size bin simulation, while reducing the associated computational cost by ~ 36 %.

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