The DOI matches its Crossref record.
Simulation of semi-explicit mechanisms of SOA formation from glyoxal in aerosol in a 3-D model
Open accessAbstract
Abstract. New pathways to form secondary organic aerosol (SOA) have been postulated recently. Glyoxal, the smallest dicarbonyl, is one of the proposed precursors. It has both anthropogenic and biogenic sources, and readily partitions into the aqueous phase of cloud droplets and deliquesced particles where it undergoes both reversible and irreversible chemistry. In this work we extend the regional scale chemistry transport model WRF-Chem to include detailed gas-phase chemistry of glyoxal formation as well as a state-of-the-science module describing its partitioning and reactions in the aerosol aqueous-phase. A comparison of several proposed mechanisms is performed to quantify the relative importance of different formation pathways and their regional variability. The CARES/CalNex campaigns over California in summer 2010 are used as case studies to evaluate the model against observations. A month-long simulation over the continental United States (US) enables us to extend our results to the continental scale. In all simulations over California, the Los Angeles (LA) basin was found to be the hot spot for SOA formation from glyoxal, which contributes between 1% and 15% of the model SOA depending on the mechanism used. Our results indicate that a mechanism based only on a reactive (surface limited) uptake coefficient leads to higher SOA yields from glyoxal compared to a more detailed description that considers aerosol phase state and chemical composition. In the more detailed simulations, surface uptake is found to give the highest SOA mass yields compared to a volume process and reversible formation. We find that the yields of the latter are limited by the availability of glyoxal in aerosol water, which is in turn controlled by an increase in the Henry's law constant depending on salt concentrations ("salting-in"). A time dependence in this increase prevents substantial partitioning of glyoxal into aerosol water at high salt concentrations. If this limitation is removed, volume pathways contribute > 20% of glyoxal-SOA mass, and the total mass formed (5.8% of total SOA in the LA basin) is about a third of the simple uptake coefficient formulation without consideration of aerosol phase state and composition. Results from the continental US simulation reveal the much larger potential to form glyoxal-SOA over the eastern continental US. Interestingly, the low concentrations of glyoxal-SOA over the western continental US are not due to the lack of a potential to form glyoxal-SOA here. Rather these small glyoxal-SOA concentrations reflect dry conditions and high salt concentrations, and the potential to form SOA mass here will strongly depend on the water associated with particles.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Formation of Urban Fine Particulate Matter
Zhang, R., Wang, G., Guo, S., Zamora, M. L., Ying, Q., Lin, Y., Wang, W., Hu, M., & Wang, Y. (2015) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00067 · Cited by 1,426
The Whole Atmosphere Community Climate Model Version 6 (WACCM6)
Gettelman, A., Mills, M. J., Kinnison, D. E., Garcia, R. R., Smith, A. K., Marsh, D. R., Tilmes, S., Vitt, F., Bardeen, C. G., McInerny, J., et al. (2019) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2019jd030943 · Cited by 786
The Chemistry Mechanism in the Community Earth System Model Version 2 (CESM2)
Emmons, L. K., Schwantes, R. H., Orlando, J. J., Tyndall, G., Kinnison, D., Lamarque, J., Marsh, D., Mills, M. J., Tilmes, S., Bardeen, C., et al. (2020) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2019ms001882 · Cited by 613
Self-citationClimate Forcing and Trends of Organic Aerosols in the Community Earth System Model (CESM2)
Tilmes, S., Hodzic, A., Emmons, L. K., Mills, M. J., Gettelman, A., Kinnison, D. E., Park, M., Lamarque, J. ‐., Vitt, F., Shrivastava, M., et al. (2019) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2019ms001827 · Cited by 246
Self-citationSchwantes, R. H., Emmons, L. K., Orlando, J. J., Barth, M. C., Tyndall, G. S., Hall, S. R., Ullmann, K., St. Clair, J. M., Blake, D. R., Wisthaler, A., et al. (2020) · Atmospheric Chemistry and Physics · doi:10.5194/acp-20-3739-2020 · Cited by 112
Self-citation
Metadata
- Authors
- Knote, C., Hodzic, A., Jimenez, J. L., Volkamer, R., Orlando, J. J., Baidar, S., Brioude, J., Fast, J., Gentner, D. R., Goldstein, A. H., Hayes, P. L., Knighton, W. B., Oetjen, H., Setyan, A., Stark, H., Thalman, R., Tyndall, G., Washenfelder, R., Waxman, E., & Zhang, Q.
- Venue
- Atmospheric Chemistry and Physics
- Publisher
- Copernicus GmbH
- Published
- 2014-06-24
- Volume
- 14
- Issue
- 12
- Pages
- 6213-6239
- ISSN
- 1680-7316 (ISSN-L)
- 1680-7324
- OpenAlex
- W2020857572
- Cited by
- 250
- References
- 0
- FWCI
- 10.37
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Simulation of semi-explicit mechanisms of SOA formation from glyoxal in aerosol in a 3-D model. https://app.cochat.ai/papers/10.5194/acp-14-6213-2014
- The paper
- Knote, C., Hodzic, A., Jimenez, J. L., Volkamer, R., Orlando, J. J., Baidar, S., Brioude, J., Fast, J., Gentner, D. R., Goldstein, A. H., Hayes, P. L., Knighton, W. B., Oetjen, H., Setyan, A., Stark, H., Thalman, R., Tyndall, G., Washenfelder, R., Waxman, E., & Zhang, Q. (2014). Simulation of semi-explicit mechanisms of SOA formation from glyoxal in aerosol in a 3-D model. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-14-6213-2014
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.