Efficiency of cloud condensation nuclei formation from ultrafine particles

By J. Pierce, P. J. Adams. 2006

195 citations recorded by the source corpus.

Atmospheric cloud condensation nuclei (CCN) concentrations are a key uncertainty in the assessment of the effect of anthropogenic aerosol on clouds and climate. The ability of new ultrafine particles to grow to become CCN varies throughout the atmosphere and must be understood in order to understand CCN formation. We have developed the Probability of Ultrafine particle Growth (PUG) model to answer questions regarding which growth and sink mechanisms control this growth, how the growth varies between different parts of the atmosphere and how uncertainties with respect to the magnitude and size distribution of ultrafine emissions translates into uncertainty in CCN generation. The inputs to the PUG model are the concentrations of condensable gases, the size distribution of ambient aerosol, particle deposition timescales and physical properties of the particles and condensable gases. It was found in most cases that condensation is the dominant growth mechanism and coagulation with larger particles is the dominant sink mechanism for ultrafine particles. In this work we found that the probability of a new ultrafine particle generating a CCN varies from <0.1% to ~90% in different parts of the atmosphere, though in the boundary layer a large fraction of ultrafine particles have a probability between 1% and 40%. Some regions, such as the tropical free troposphere, are areas with high probabilities; however, variability within regions makes it difficult to predict which regions of the atmosphere are most efficient for generating CCN from ultrafine particles. For a given mass of primary ultrafine aerosol, an uncertainty of a factor of two in the modal diameter can lead to an uncertainty in the number of CCN generated as high as a factor for eight. It was found that no single moment of the primary aerosol size distribution, such as total mass or number, is a robust predictor of the number of CCN ultimately generated. Therefore, a complete description of the emissions size distribution is generally required for global aerosol microphysics models.

Subfields: Atmospheric Science, Global and Planetary Change, Health, Toxicology and Mutagenesis

View Paper: https://www.semanticscholar.org/paper/6fa3f29c117ef1cca6d431fb91c2b13eb693acd2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

In Global and Planetary Change

In Health, Toxicology and Mutagenesis

Citations in the corpus

Determination of cloud condensation nuclei production from measured new particle formation events (2009, methodology): “Previous studies modeling CCN formation from ultrafine particle emissions [Pierce and Adams, 2007] assume sulfuric acid vapor as the only condensing species contributing to particle growth and use either measured or modeled sulfuric acid vapor concentration to model growth rates.”
JournalofGeophysicalResearch : Atmospheres Causes and importance of new particle formation in the present-day and preindustrial atmospheres (2017, unknown): “However, this estimate will be biased toward regions where NPF rates are high, which may not necessarily be where CCN formation is efficient [Pierce and Adams, 2007].”
Impact of nucleation on global CCN (2009, background): “…complex ways to variations in precursor gases and existing particle concentrations (Gaydos et al., 2005; Spracklen et al., 2006; Jung et al., 2006; Pierce and Adams, 2007; Wang and Penner, 2009) and other environmental factors that are still not completely understood (Lyubovtseva et al., 2005;…”
Cloud condensation nuclei production associated with atmospheric nucleation: a synthesis based on existing literature and new results (2012, background): “10 The likelihood that nucleated particles will grow to CCN sizes, called also the CCN formation efficiency, depends on the competition between the rates of growth and removal processes (Kerminen et al., 2004; Pierce and Adams, 2007).”
The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei (2013, background): “Previous studies have shown this to be an important source of global CCN (Spracklen et al., 2005b; Pierce and Adams, 2006; Luo and Yu, 2011), but other studies suggest a more limited effect (Stier et al., 2006).”
Aerosol cloud precipitation interactions. Part 1. The nature and sources of cloud-active aerosols (2008, background): “The alternative mechanism for increasing the number of particles in the atmosphere is nucleation from the gas phase (Pierce and Adams, 2007), a process that is still poorly understood despite extensive research over the last decades.”
Uncertainty in global CCN concentrations from uncertain aerosol nucleation and primary emission rates (2008, methodology): “Nucleation and condensation rates are now calculated simultaneously using the pseudo-steady-state approximation (PSSA) for sulfuric acid vapor (Pierce and Adams, 2009). In general, this greatly increases the length of time steps allowed while still simulating accurately the nucleation rates, thus de”
Can cosmic rays affect cloud condensation nuclei by altering new particle formation rates? (2009, methodology): “Because we have only simulated present-day conditions, the role of cosmic rays on CCN prior to present-day conditions remains uncertain, although Pierce and Adams [2009] found that the sensitivity of CCN to nucleation was similar between pre-industrial and present-day simulations. Regardless, any ch”