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Simulation of the size-composition distribution of atmospheric nanoparticles over Europe

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submitted on 2024-05-30, 11:02 and posted on 2024-05-30, 11:02 authored by David Patoulias, Christos Fountoukis, Ilona Riipinen, Ari Asmi, Markku Kulmala, Spyros N. Pandis

PMCAMx-UF, a three-dimensional chemical transport model focusing on the simulation of the ultrafine particle size distribution and composition has been extended with the addition of the volatility basis set (VBS) approach for the simulation of organic aerosol (OA). The model was applied in Europe to quantify the effect of secondary semi-volatile organic vapors on particle number concentrations. The model predictions were evaluated against field observations collected during the PEGASOS 2012 campaign. The measurements included both ground and airborne measurements, from stations across Europe and a zeppelin measuring above Po Valley. The ground level concentrations of particles with a diameter larger than 100 nm (N100) were reproduced with a daily normalized mean error of 40 % and a daily normalized mean bias of −20 %. PMCAMx-UF tended to overestimate the concentration of particles with a diameter larger than 10 nm (N10) with a daily normalized mean bias of 75 %. The model was able to reproduce, within a factor of 2, 85 % of the N10 and 75 % of the N100 zeppelin measurements above ground. The condensation of organics led to an increase (50 %–120 %) in the N100 concentration mainly in central and northern Europe, while the N10 concentration decreased by 10 %–30 %. Including the VBS in PMCAMx-UF improved its ability to simulate aerosol number concentration compared to simulations neglecting organic condensation on ultrafine particles.


Other Information

Published in: Atmospheric Chemistry and Physics
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.5194/acp-18-13639-2018

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Copernicus

Publication Year

  • 2018

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • Qatar Environment and Energy Research Institute - HBKU

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