Dataset Information

Cloud droplet activation of organic-salt mixtures predicted from two model treatments of the droplet surface.

ABSTRACT: The droplet surface plays important roles in the interaction between organic aerosols with clouds and climate. Surface active organic compounds can partition to the droplet surface, depleting the solute from the droplet bulk or depressing the droplet surface tension. This may in turn affect the shape of the droplet growth curve, threshold of aerosol activation into cloud droplets, activated droplet size distributions, and cloud radiative effects. In this work, a new monolayer model along with a traditional Gibbs adsorption isotherm model was used in conjunction with equilibrium Köhler theory to predict cloud condensation nuclei (CCN) activation of both simple and complex surface active model aerosol systems. For the surface active aerosol considered, the monolayer droplet model produces similar results to the Gibbs model as well as comparable results to CCN measurements from the literature, even for systems where specific molecular identities and aqueous properties are unknown. The monolayer model is self-contained and fully prognostic, and provides a versatile, conceptually simple, yet physically based model for understanding the role of organic surfactants in cloud droplet formation.

SUBMITTER: Lin JJ

PROVIDER: S-EPMC6716451 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Cloud droplet activation of organic-salt mixtures predicted from two model treatments of the droplet surface.

Lin Jack J JJ Malila Jussi J Prisle Nønne L NL

Environmental science. Processes & impacts 20181101 11

The droplet surface plays important roles in the interaction between organic aerosols with clouds and climate. Surface active organic compounds can partition to the droplet surface, depleting the solute from the droplet bulk or depressing the droplet surface tension. This may in turn affect the shape of the droplet growth curve, threshold of aerosol activation into cloud droplets, activated droplet size distributions, and cloud radiative effects. In this work, a new monolayer model along with a ...[more]

PMID: 30398264

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Project description:AtGenExpress: A multinational coordinated effort to uncover the transcriptome of the multicellular model organism Arabidopsis thaliana The activity of genes and their encoded products can be regulated in several ways, but transcription is the primary level, since all other modes of regulation (RNA splicing, RNA and protein stability, etc.) are dependent on a gene being transcribed in the first place. The importance of transcriptional regulation has been underscored by the recent flood of global expression analyses, which have confirmed that transcriptional co-regulation of genes that act together is the norm, not the exception. Moreover, many studies suggest that evolutionary change is driven in large part by modifications of transcriptional programs. An essential first step toward deciphering the transcriptional code is to determine the expression pattern of all genes. With this goal in mind, an international effort to develop a gene expression atlas of Arabidopsis has been underway since fall 2003. This project, dubbed AtGenExpress, is funded by the DFG, and will provide the Arabidopsis community with access to a large set of Affymetrix microarray data. As part of this collaboration, we have generated expression data from 80 biologicaly different samples in triplicate. Seeds of Arabidopsis thaliana Wild Type (col-0) were sown on rafts in Magenta boxes containing MS-Agar-media. After 2 days in the cold room (4°C, dark) the boxes were transferred to the long day chamber. Long day conditions were 16/8 hrs light/dark, 24°C, 50% humidity and 150 µEinstein/cm2 sec light intensity. At day 11 the rafts were transferred in Magenta boxes containing MS-liquid-media. At day 16 stress treatment started at 3 hrs of light period; samples taken at 0.5, 1, 3, 6, 12, 24 h after treatment (in selected indicated cases 0.25h and 4.0h too), control samples include 0h; roots and shoots were prepared separately; all treatments and preparations were done on the same batch of seedlings in one place (Lab J.Kudla/Ulm, Germany) by coworkers from the indicated groups. Experimenter name = Cecilia D`Angelo , Joachim Kilian , Joerg Kudla , Oliver Batistic , Stefan Weinl Experimenter institute = AtGenExpress Keywords: time_series_design; growth_condition_design; stimulus_or_stress_design

Dataset Information

Cloud droplet activation of organic-salt mixtures predicted from two model treatments of the droplet surface.

Publications

Cloud droplet activation of organic-salt mixtures predicted from two model treatments of the droplet surface.

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