Dataset Information

Comparison of the SAWNUC model with CLOUD measurements of sulphuric acid-water nucleation.

ABSTRACT: Binary nucleation of sulphuric acid-water particles is expected to be an important process in the free troposphere at low temperatures. SAWNUC (Sulphuric Acid Water Nucleation) is a model of binary nucleation that is based on laboratory measurements of the binding energies of sulphuric acid and water in charged and neutral clusters. Predictions of SAWNUC are compared for the first time comprehensively with experimental binary nucleation data from the CLOUD chamber at European Organization for Nuclear Research. The experimental measurements span a temperature range of 208-292 K, sulphuric acid concentrations from 1·10⁶ to 1·10⁹ cm^-3, and distinguish between ion-induced and neutral nucleation. Good agreement, within a factor of 5, is found between the experimental and modeled formation rates for ion-induced nucleation at 278 K and below and for neutral nucleation at 208 and 223 K. Differences at warm temperatures are attributed to ammonia contamination which was indicated by the presence of ammonia-sulphuric acid clusters, detected by an Atmospheric Pressure Interface Time of Flight (APi-TOF) mass spectrometer. APi-TOF measurements of the sulphuric acid ion cluster distributions ( (H2SO4)i·HSO4- with i = 0, 1, ..., 10) show qualitative agreement with the SAWNUC ion cluster distributions. Remaining differences between the measured and modeled distributions are most likely due to fragmentation in the APi-TOF. The CLOUD results are in good agreement with previously measured cluster binding energies and show the SAWNUC model to be a good representation of ion-induced and neutral binary nucleation of sulphuric acid-water clusters in the middle and upper troposphere.

SUBMITTER: Ehrhart S

PROVIDER: S-EPMC5302017 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of the SAWNUC model with CLOUD measurements of sulphuric acid-water nucleation.

Ehrhart Sebastian S Ickes Luisa L Almeida Joao J Amorim Antonio A Barmet Peter P Bianchi Federico F Bianchi Federico F Dommen Josef J Dunne Eimear M EM Duplissy Jonathan J Franchin Alessandro A Kangasluoma Juha J Kirkby Jasper J Kürten Andreas A Kupc Agnieszka A Lehtipalo Katrianne K Nieminen Tuomo T Riccobono Francesco F Rondo Linda L Schobesberger Siegfried S Steiner Gerhard G Tomé António A Wimmer Daniela D Baltensperger Urs U Wagner Paul E PE Curtius Joachim J

Journal of geophysical research. Atmospheres : JGR 20161001 20

Binary nucleation of sulphuric acid-water particles is expected to be an important process in the free troposphere at low temperatures. SAWNUC (Sulphuric Acid Water Nucleation) is a model of binary nucleation that is based on laboratory measurements of the binding energies of sulphuric acid and water in charged and neutral clusters. Predictions of SAWNUC are compared for the first time comprehensively with experimental binary nucleation data from the CLOUD chamber at European Organization for Nu ...[more]

PMID: 28239533

Similar Datasets

Project description:Aerosol-cloud interactions are the largest source of uncertainty in quantifying anthropogenic radiative forcing. The large uncertainty is, in part, due to the difficulty of predicting cloud microphysical parameters, such as the cloud droplet number concentration (N d). Even though rigorous first-principle approaches exist to calculate N d, the cloud and aerosol research community also relies on empirical approaches such as relating N d to aerosol mass concentration. Here we analyze relationships between N d and cloud water chemical composition, in addition to the effect of environmental factors on the degree of the relationships. Warm, marine, stratocumulus clouds off the California coast were sampled throughout four summer campaigns between 2011 and 2016. A total of 385 cloud water samples were collected and analyzed for 80 chemical species. Single- and multispecies log-log linear regressions were performed to predict N d using chemical composition. Single-species regressions reveal that the species that best predicts N d is total sulfate ( Radj2=0.40 ). Multispecies regressions reveal that adding more species does not necessarily produce a better model, as six or more species yield regressions that are statistically insignificant. A commonality among the multispecies regressions that produce the highest correlation with N d was that most included sulfate (either total or non-sea-salt), an ocean emissions tracer (such as sodium), and an organic tracer (such as oxalate). Binning the data according to turbulence, smoke influence, and in-cloud height allowed for examination of the effect of these environmental factors on the composition-N d correlation. Accounting for turbulence, quantified as the standard deviation of vertical wind speed, showed that the correlation between N d with both total sulfate and sodium increased at higher turbulence conditions, consistent with turbulence promoting the mixing between ocean surface and cloud base. Considering the influence of smoke significantly improved the correlation with N d for two biomass burning tracer species in the study region, specifically oxalate and iron. When binning by in-cloud height, non-sea-salt sulfate and sodium correlated best with N d at cloud top, whereas iron and oxalate correlated best with N d at cloud base.

Dataset Information

Comparison of the SAWNUC model with CLOUD measurements of sulphuric acid-water nucleation.

Publications

Comparison of the SAWNUC model with CLOUD measurements of sulphuric acid-water nucleation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets