Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.414
IF5.414
IF 5-year value: 5.958
IF 5-year
5.958
CiteScore value: 9.7
CiteScore
9.7
SNIP value: 1.517
SNIP1.517
IPP value: 5.61
IPP5.61
SJR value: 2.601
SJR2.601
Scimago H <br class='widget-line-break'>index value: 191
Scimago H
index
191
h5-index value: 89
h5-index89
Preprints
https://doi.org/10.5194/acp-2020-756
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-756
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Aug 2020

12 Aug 2020

Review status
This preprint is currently under review for the journal ACP.

A global model perturbed parameter ensemble study of secondary organic aerosol formation

Kamalika Sengupta1, Kirsty Pringle1, Jill S. Johnson1, Carly Reddington1, Jo Browse2, Catherine E. Scott1, and Ken Carslaw1 Kamalika Sengupta et al.
  • 1Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
  • 2Center for Geography and Environmental Science, University of Exeter, Penryn, Cornwall, UK

Abstract. A global model perturbed parameter ensemble of 60 simulations was used to explore how combinations of six parameters related to secondary organic aerosol (SOA) formation affect particle number concentrations and organic aerosol mass. The parameters represent the formation of organic compounds with different volatilities from biogenic and anthropogenic sources. The most plausible parameter combinations were determined by comparing the simulations against observations of the number concentration of particles larger than 3 nm diameter (N3), the number concentration of particles larger than 50 nm diameter (N50), and the organic aerosol (OA) mass concentration. The simulations expose a high degree of model equifinality in which the skill of widely different parameter combinations cannot be distinguished against observations. We therefore conclude that, based on the observations we have used, a 6-parameter SOA scheme is under-determined. Nevertheless, the model skill in simulating N3 and N50 is clearly determined by the low and extremely low volatility compounds that affect new particle formation and growth, and the skill in simulating OA mass is determined by the low volatility and semi-volatile compounds. The biogenic low volatility class of compounds that grow nucleated clusters and condense on all particles is found to have the strongest effect on the model skill in simulating N3, N50 and OA. The simulations also expose potential structural deficiencies in the model: we find that parameter combinations that are best for N3 and N50 are worst for OA mass, and the ensemble exaggerates the observed seasonal cycle of particle concentrations – a deficiency that we conclude requires an additional anthropogenic source of either primary or secondary particles.

Kamalika Sengupta et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Kamalika Sengupta et al.

Kamalika Sengupta et al.

Viewed

Total article views: 207 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
144 60 3 207 3 1
  • HTML: 144
  • PDF: 60
  • XML: 3
  • Total: 207
  • BibTeX: 3
  • EndNote: 1
Views and downloads (calculated since 12 Aug 2020)
Cumulative views and downloads (calculated since 12 Aug 2020)

Viewed (geographical distribution)

Total article views: 137 (including HTML, PDF, and XML) Thereof 137 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 21 Oct 2020
Publications Copernicus
Download
Short summary
Global models consistently underestimate atmospheric secondary organic aerosol (SOA), which have significant climatic implications. We use a perturbed parameter model ensemble and ground-based observations to reduce the uncertainty in modelling SOA formation from oxidation of volatile organic compounds. We identify plausible parameter spaces for the yields of extremely low volatility, low volatility and semi-volatile organic compounds based on model-observation match for three key model outputs.
Global models consistently underestimate atmospheric secondary organic aerosol (SOA), which have...
Citation
Altmetrics