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Surface tension prevails over solute effect in organic-influenced cloud droplet activation

Overview of attention for article published in Nature, June 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)

Mentioned by

news
2 news outlets
twitter
35 tweeters
facebook
2 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
132 Dimensions

Readers on

mendeley
175 Mendeley
citeulike
1 CiteULike
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Title
Surface tension prevails over solute effect in organic-influenced cloud droplet activation
Published in
Nature, June 2017
DOI 10.1038/nature22806
Pubmed ID
Authors

Jurgita Ovadnevaite, Andreas Zuend, Ari Laaksonen, Kevin J. Sanchez, Greg Roberts, Darius Ceburnis, Stefano Decesari, Matteo Rinaldi, Natasha Hodas, Maria Cristina Facchini, John H. Seinfeld, Colin O’ Dowd

Abstract

The spontaneous growth of cloud condensation nuclei (CCN) into cloud droplets under supersaturated water vapour conditions is described by classic Köhler theory. This spontaneous activation of CCN depends on the interplay between the Raoult effect, whereby activation potential increases with decreasing water activity or increasing solute concentration, and the Kelvin effect, whereby activation potential decreases with decreasing droplet size or increases with decreasing surface tension, which is sensitive to surfactants. Surface tension lowering caused by organic surfactants, which diminishes the Kelvin effect, is expected to be negated by a concomitant reduction in the Raoult effect, driven by the displacement of surfactant molecules from the droplet bulk to the droplet-vapour interface. Here we present observational and theoretical evidence illustrating that, in ambient air, surface tension lowering can prevail over the reduction in the Raoult effect, leading to substantial increases in cloud droplet concentrations. We suggest that consideration of liquid-liquid phase separation, leading to complete or partial engulfing of a hygroscopic particle core by a hydrophobic organic-rich phase, can explain the lack of concomitant reduction of the Raoult effect, while maintaining substantial lowering of surface tension, even for partial surface coverage. Apart from the importance of particle size and composition in droplet activation, we show by observation and modelling that incorporation of phase-separation effects into activation thermodynamics can lead to a CCN number concentration that is up to ten times what is predicted by climate models, changing the properties of clouds. An adequate representation of the CCN activation process is essential to the prediction of clouds in climate models, and given the effect of clouds on the Earth's energy balance, improved prediction of aerosol-cloud-climate interactions is likely to result in improved assessments of future climate change.

Twitter Demographics

The data shown below were collected from the profiles of 35 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 175 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Unknown 174 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 30%
Researcher 34 19%
Student > Master 19 11%
Student > Doctoral Student 10 6%
Professor > Associate Professor 10 6%
Other 24 14%
Unknown 26 15%
Readers by discipline Count As %
Chemistry 40 23%
Environmental Science 27 15%
Earth and Planetary Sciences 22 13%
Engineering 18 10%
Physics and Astronomy 15 9%
Other 18 10%
Unknown 35 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 38. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 August 2019.
All research outputs
#681,549
of 17,819,859 outputs
Outputs from Nature
#25,382
of 80,457 outputs
Outputs of similar age
#18,123
of 275,969 outputs
Outputs of similar age from Nature
#562
of 796 outputs
Altmetric has tracked 17,819,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 80,457 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 90.7. This one has gotten more attention than average, scoring higher than 68% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 275,969 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 796 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.