The DOI matches its Crossref record; 87 of the 87 references it cites were found in a registry or an index.
Glyoxal processing by aerosol multiphase chemistry: towards a kinetic modeling framework of secondary organic aerosol formation in aqueous particles
Open accessAbstract
Abstract. This study presents a modeling framework based on laboratory data to describe the kinetics of glyoxal reactions that form secondary organic aerosol (SOA) in aqueous aerosol particles. Recent laboratory results on glyoxal reactions are reviewed and a consistent set of empirical reaction rate constants is derived that captures the kinetics of glyoxal hydration and subsequent reversible and irreversible reactions in aqueous inorganic and water-soluble organic aerosol seeds. Products of these processes include (a) oligomers, (b) nitrogen-containing products, (c) photochemical oxidation products with high molecular weight. These additional aqueous phase processes enhance the SOA formation rate in particles and yield two to three orders of magnitude more SOA than predicted based on reaction schemes for dilute aqueous phase (cloud) chemistry for the same conditions (liquid water content, particle size). The application of the new module including detailed chemical processes in a box model demonstrates that both the time scale to reach aqueous phase equilibria and the choice of rate constants of irreversible reactions have a pronounced effect on the predicted atmospheric relevance of SOA formation from glyoxal. During day time, a photochemical (most likely radical-initiated) process is the major SOA formation pathway forming ∼5 μg m−3 SOA over 12 h (assuming a constant glyoxal mixing ratio of 300 ppt). During night time, reactions of nitrogen-containing compounds (ammonium, amines, amino acids) contribute most to the predicted SOA mass; however, the absolute predicted SOA masses are reduced by an order of magnitude as compared to day time production. The contribution of the ammonium reaction significantly increases in moderately acidic or neutral particles (5 < pH < 7). Glyoxal uptake into ammonium sulfate seed under dark conditions can be represented with a single reaction parameter keffupt that does not depend on aerosol loading or water content, which indicates a possibly catalytic role of aerosol water in SOA formation. However, the reversible nature of uptake under dark conditions is not captured by keffupt, and can be parameterized by an effective Henry's law constant including an equilibrium constant Kolig = 1000 (in ammonium sulfate solution). Such reversible glyoxal oligomerization contributes <1% to total predicted SOA masses at any time. Sensitivity tests reveal five parameters that strongly affect the predicted SOA mass from glyoxal: (1) time scales to reach equilibrium states (as opposed to assuming instantaneous equilibrium), (2) particle pH, (3) chemical composition of the bulk aerosol, (4) particle surface composition, and (5) particle liquid water content that is mostly determined by the amount and hygroscopicity of aerosol mass and to a lesser extent by the ambient relative humidity. Glyoxal serves as an example molecule, and the conclusions about SOA formation in aqueous particles can serve for comparative studies of other molecules that form SOA as the result of multiphase chemical processing in aerosol water. This SOA source is currently underrepresented in atmospheric models; if included it is likely to bring SOA predictions (mass and O/C ratio) into better agreement with field observations.
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
Cites
CRC Handbook of Chemistry and Physics
(2014) · doi:10.1201/b17118 · Cited by 57,706
Evolution of Organic Aerosols in the Atmosphere
Jimenez, J. L., Canagaratna, M. R., Donahue, N. M., Prevot, A. S. H., Zhang, Q., Kroll, J. H., DeCarlo, P. F., Allan, J. D., Coe, H., Ng, N. L., et al. (2009) · Science · doi:10.1126/science.1180353 · Cited by 4,167
A single parameter representation of hygroscopic growth and cloud condensation nucleus activity
Petters, M. D., & Kreidenweis, S. M. (2007) · Atmospheric Chemistry and Physics · doi:10.5194/acp-7-1961-2007 · Cited by 2,665
Reactivity of HO2/O− 2 radicals in aqueous solution
Bielski, B. H. J., Cabelli, D. E., Arudi, R. L., & Ross, A. B. (1985) · Journal of Physical and Chemical Reference Data · doi:10.1063/1.555739 · Cited by 2,169
Rethinking Organic Aerosols: Semivolatile Emissions and Photochemical Aging
Robinson, A. L., Donahue, N. M., Shrivastava, M. K., Weitkamp, E. A., Sage, A. M., Grieshop, A. P., Lane, T. E., Pierce, J. R., & Pandis, S. N. (2007) · Science · doi:10.1126/science.1133061 · Cited by 1,943
Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation Number 18
Burkholder, J. B., Sander, S. P., Abbatt, J. P. D., Barker, J. R., Huie, R. E., Kolb, C. E., Kurylo, M. J., Orkin, V. L., Wilmouth, D. M., & Wine, P. H. (2015) · doi:10.13140/rg.2.1.2504.2806 · Cited by 1,928
Gas/Particle Partitioning and Secondary Organic Aerosol Yields
Odum, J. R., Hoffmann, T., Bowman, F., Collins, D., Flagan, R. C., & Seinfeld, J. H. (1996) · Environmental Science & Technology · doi:10.1021/es950943+ · Cited by 1,529
Formation of Secondary Organic Aerosols Through Photooxidation of Isoprene
Claeys, M., Graham, B., Vas, G., Wang, W., Vermeylen, R., Pashynska, V., Cafmeyer, J., Guyon, P., Andreae, M. O., Artaxo, P., et al. (2004) · Science · doi:10.1126/science.1092805 · Cited by 1,501
CRC Handbook of Chemistry and Physics, 2009−2010, 90th ed.
(2009) · Journal of the American Chemical Society · doi:10.1021/ja906434c · Cited by 1,494
An absorption model of gas/particle partitioning of organic compounds in the atmosphere
Pankow, J. F. (1994) · Atmospheric Environment · doi:10.1016/1352-2310(94)90093-0 · Cited by 1,463
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
Pöschl, U., & Shiraiwa, M. (2015) · Chemical Reviews · doi:10.1021/cr500487s · Cited by 657
A two-dimensional volatility basis set – Part 2: Diagnostics of organic-aerosol evolution
Donahue, N. M., Kroll, J. H., Pandis, S. N., & Robinson, A. L. (2012) · Atmospheric Chemistry and Physics · doi:10.5194/acp-12-615-2012 · Cited by 657
De Haan, D. O., Hawkins, L. N., Kononenko, J. A., Turley, J. J., Corrigan, A. L., Tolbert, M. A., & Jimenez, J. L. (2011) · Environmental Science & Technology · doi:10.1021/es102933x · Cited by 299
Metadata
- Authors
- Ervens, B., & Volkamer, R.
- Venue
- Atmospheric Chemistry and Physics
- Publisher
- Copernicus GmbH
- Published
- 2010-09-02
- Volume
- 10
- Issue
- 17
- Pages
- 8219-8244
- ISSN
- 1680-7316 (ISSN-L)
- 1680-7324
- OpenAlex
- W2097806302
- Cited by
- 386
- References
- 87
- FWCI
- 20.15
- 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: Glyoxal processing by aerosol multiphase chemistry: towards a kinetic modeling framework of secondary organic aerosol formation in aqueous particles. https://app.cochat.ai/papers/10.5194/acp-10-8219-2010
- The paper
- Ervens, B., & Volkamer, R. (2010). Glyoxal processing by aerosol multiphase chemistry: towards a kinetic modeling framework of secondary organic aerosol formation in aqueous particles. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-10-8219-2010
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.