A model prediction of the yield of cloud condensation nuclei from coastal nucleation events

Liisa Pirjola, Colin D. O'Dowd, Markku Kulmala

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

30 Citations (Scopus)

Abstract

The formation and evolution of new particles during coastal nucleation events are examined using the aerosol dynamic and gas-phase chemistry model AEROFOR2. Coastal regions are known to be a strong source of natural aerosol particles and are also strong sources of biogenic vapors which can condense onto aerosol particles, thus resulting in particle growth. A number of model simulations were performed to determine the instantaneous nucleation rate along with the source rate of a generic biogenic vapor leading to the observed particle size distributions which indicate the rapid appearance of ∼10 5-106 cm-3 nucleation mode particles in this environment. Model calculations suggest values of 3 × 105 cm-3 s-1 to 3 × 106 cm-3 s-1 for the instantaneous nucleation rate and a value of 5 × 107 cm-3 s-1 for the condensable vapor source rate in order to reproduce the observed concentrations. A significant fraction of these new particles survive to grow into cloud condensation nuclei (CCN) sizes for supersaturations typically encountered in boundary layer clouds during subsequent evolution over 3 days under clear-sky conditions, thus contributing to the indirect radiative effect of aerosols. The amount of CCN is mainly affected by coagulation between particles and condensation of the biogenic vapor and, to a lesser extent, by condensation of sulphuric acid formed by DMS oxidation. In all simulated cases, an increase of more than 100% in CCN concentration, for supersaturations >0.35% was observed.

Original languageEnglish
Article number8098
JournalJournal of Geophysical Research
Volume107
Issue number19
DOIs
Publication statusPublished - Oct 2002

Fingerprint

Dive into the research topics of 'A model prediction of the yield of cloud condensation nuclei from coastal nucleation events'. Together they form a unique fingerprint.

Cite this