Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Formation of late-generation atmospheric compounds inhibited by rapid deposition

Nature Geoscience volume 18, pages 213–218 (2025)Cite this article

Subjects

Abstract

Reactive organic carbon species are important fuel for atmospheric chemical reactions, including the formation of secondary organic aerosol. However, in parallel to atmospheric oxidation processes, deposition can remove compounds from the atmosphere and impact downstream environments. To understand the impact of deposition on atmospheric oxidation, we present a framework for predicting and visualizing the fate of a molecule on the basis of the physicochemical properties of compounds (Henry’s law constant, vapour pressure and reaction rate constants), which are used to estimate timescales for oxidation and deposition. By implementing our deposition rates in chemical models, we show that deposition substantially suppresses atmospheric reactivity and aerosol formation by removing early-generation products and preventing the formation of large fractions (up to 90%) of downstream, late-generation compounds. Deposition is frequently missing in the laboratory experiments and detailed chemical modelling, which probably biases our understanding of atmospheric composition.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Prediction of the fate of a molecule based on its H and OH reaction rate constant.
Fig. 2: Modelled oxidation and deposition timescales of atmospheric oxidation products.
Fig. 3: Impact of deposition on modelled organic aerosol formation and OH reactivity in a chemically explicit model.
Fig. 4: Impact of deposition on the modelled organic aerosol formation in a volatility-binned box model.
Fig. 5: Concentrations of gas- and particle-phase oxidation products categorized by their oxidation generation under model conditions with and without considering deposition.
Fig. 6: Removal of compounds due to deposition as a function of oxidation generation.

Similar content being viewed by others

Data availability

The lifetimes and physicochemical properties of the compounds shown in Fig. 2 and ~140,000 additional compounds are publicly available via Mendeley (https://doi.org/10.17632/3rgvkf7c9n) (ref. 27). The compounds used in the chemically explicit modelling are freely available through the Master Chemical Mechanism (https://mcm.york.ac.uk/MCM/) and referenced publicly available works. Deposition lifetimes for all compounds used in the chemically explicit box model are provided as Supplementary Dataset 1. These data and the referenced publicly available models were used to generate Figs. 3, 5 and 6 and Extended Data Figs. 2–4. All information to generate Figs. 1 and 4 is described in Methods and Supplementary Information. Source data are provided with this paper.

Code availability

Models used in this work are publicly available as cited. The F0AM model was used as provided, with additional reactions added as described in the article and Supplementary Information. The SimpleSOM model was modified slightly to include deposition as described in the article; the modified code has been provided to the authors of the model for inclusion in their next publicly available release.

References

  1. Burnett, R. T. et al. An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environ. Health Perspect. 122, 397–403 (2014).

    Google Scholar 

  2. Heald, C. L. & Kroll, J. H. The fuel of atmospheric chemistry: toward a complete description of reactive organic carbon. Sci. Adv. 6, eaay8967 (2020).

    CAS  Google Scholar 

  3. Jin, L. et al. Constraining emissions of volatile organic compounds from western US wildfires with WE-CAN and FIREX-AQ airborne observations. Atmos. Chem. Phys. 23, 5969–5991 (2023).

    CAS  Google Scholar 

  4. Guenther, A. B. et al. The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions. Geosci. Model Dev. 5, 1471–1492 (2012).

    Google Scholar 

  5. Murphy, B. N. et al. Reactive organic carbon air emissions from mobile sources in the United States. Atmos. Chem. Phys. 23, 13469–13483 (2023).

    CAS  Google Scholar 

  6. Mattila, J. M. et al. Contrasting chemical complexity and the reactive organic carbon budget of indoor and outdoor air. Environ. Sci. Technol. 56, 109–118 (2022).

    CAS  Google Scholar 

  7. McDonald, B. C. et al. Volatile chemical products emerging as largest petrochemical source of urban organic emissions. Science 359, 760–764 (2018).

    CAS  Google Scholar 

  8. Seltzer, K. M. et al. Reactive organic carbon emissions from volatile chemical products. Atmos. Chem. Phys. 21, 5079–5100 (2021).

    CAS  Google Scholar 

  9. Isaacman-Vanwertz, G. et al. Chemical evolution of atmospheric organic carbon over multiple generations of oxidation. Nat. Chem. 10, 462–468 (2018).

    CAS  Google Scholar 

  10. Goldstein, A. H. & Galbally, I. E. Known and unexplored organic constituents in the Earth’s atmosphere. Environ. Sci. Technol. 41, 1514–1521 (2007).

    CAS  Google Scholar 

  11. Aumont, B., Szopa, S. & Madronich, S. Modelling the evolution of organic carbon during its gas-phase tropospheric oxidation: development of an explicit model based on a self generating approach. Atmos. Chem. Phys. 5, 2497–2517 (2005).

    CAS  Google Scholar 

  12. Bi, C. & Isaacman-VanWertz, G. Estimated timescales for wet deposition of organic compounds as a function of Henry’s law constants. Environ. Sci. Atmos. 2, 1526–1533 (2022).

    CAS  Google Scholar 

  13. Hodzic, A. et al. Volatility dependence of Henry’s law constants of condensable organics: application to estimate depositional loss of secondary organic aerosols. Geophys. Res. Lett. 41, 4795–4804 (2014).

    CAS  Google Scholar 

  14. Isaacman-VanWertz, G. & Aumont, B. Impact of organic molecular structure on the estimation of atmospherically relevant physicochemical parameters. Atmos. Chem. Phys. 21, 6541–6563 (2021).

    CAS  Google Scholar 

  15. Safieddine, S. A., Heald, C. L. & Henderson, B. H. The global nonmethane reactive organic carbon budget: a modeling perspective. Geophys. Res. Lett. 44, 3897–3906 (2017).

    CAS  Google Scholar 

  16. Pye, H. O. T. et al. Linking gas, particulate, and toxic endpoints to air emissions in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM). Atmos. Chem. Phys. 23, 5043–5099 (2023).

    CAS  Google Scholar 

  17. Carter, W. P. L. Development of the SAPRC-07 chemical mechanism. Atmos. Environ. 44, 5324–5335 (2010).

    CAS  Google Scholar 

  18. Sarwar, G. et al. A comparison of atmospheric composition using the Carbon Bond and Regional Atmospheric Chemistry Mechanisms. Atmos. Chem. Phys. 13, 9695–9712 (2013).

    Google Scholar 

  19. Donahue, N. M., Epstein, S. A., Pandis, S. N. & Robinson, A. L. A two-dimensional volatility basis set: 1. Organic-aerosol mixing thermodynamics. Atmos. Chem. Phys. 11, 3303–3318 (2011).

    CAS  Google Scholar 

  20. Kroll, J. H. et al. Carbon oxidation state as a metric for describing the chemistry of atmospheric organic aerosol. Nat. Chem. 3, 133–139 (2011).

    CAS  Google Scholar 

  21. Heald, C. L. et al. A simplified description of the evolution of organic aerosol composition in the atmosphere. Geophys. Res. Lett. 37, L08803 (2010).

    Google Scholar 

  22. Cappa, C. D. & Wilson, K. R. Multi-generation gas-phase oxidation, equilibrium partitioning, and the formation and evolution of secondary organic aerosol. Atmos. Chem. Phys. 12, 9505–9528 (2012).

    CAS  Google Scholar 

  23. Pankow, J. F. & Barsanti, K. C. The carbon number–polarity grid: a means to manage the complexity of the mix of organic compounds when modeling atmospheric organic particulate matter. Atmos. Environ. 43, 2829–2835 (2009).

    CAS  Google Scholar 

  24. Estimation Programs Interface Suite for Microsoft Windows v.4.11 (EPA, 2012).

  25. Compernolle, S., Ceulemans, K. & Müller, J. F. EVAPORATION: a new vapour pressure estimation method for organic molecules including non-additivity and intramolecular interactions. Atmos. Chem. Phys. 11, 9431–9450 (2011).

    CAS  Google Scholar 

  26. Nguyen, T. B. et al. Rapid deposition of oxidized biogenic compounds to a temperate forest. Proc. Natl Acad. Sci. USA 112, E392–E401 (2015).

    CAS  Google Scholar 

  27. Isaacman-VanWertz, G. & Aumont, B. SMILES and Physicochemical Parameters—Pinene, Decane, Toluene Oxidation Products v.2 (Mendeley Data, 2021).

  28. Wolfe, G. M., Marvin, M. R., Roberts, S. J., Travis, K. R. & Liao, J. The Framework for 0-D Atmospheric Modeling (F0AM) v3.1. Geosci. Model Dev. 9, 3309–3319 (2016).

    Google Scholar 

  29. Pye, H. O. T. et al. Anthropogenic enhancements to production of highly oxygenated molecules from autoxidation. Proc. Natl Acad. Sci. USA 116, 6641–6646 (2019).

    CAS  Google Scholar 

  30. Li, J. et al. Observational constraints on glyoxal production from isoprene oxidation and its contribution to organic aerosol over the southeast United States. J. Geophys. Res. Atmos. 121, 9849–9861 (2016).

    CAS  Google Scholar 

  31. Zhu, Y. et al. Multiphase MCM–CAPRAM modeling of the formation and processing of secondary aerosol constituents observed during the Mt Tai summer campaign in 2014. Atmos. Chem. Phys. 20, 6725–6747 (2020).

    CAS  Google Scholar 

  32. Jathar, S. H. et al. A computationally efficient model to represent the chemistry, thermodynamics, and microphysics of secondary organic aerosols (simpleSOM): model development and application to α-pinene SOA. Environ. Sci. Atmos. 1, 372–394 (2021).

    CAS  Google Scholar 

  33. Knote, C., Hodzic, A. & Jimenez, J. L. The effect of dry and wet deposition of condensable vapors on secondary organic aerosols concentrations over the continental US. Atmos. Chem. Phys. 15, 1–18 (2015).

    Google Scholar 

  34. Ng, N. L. et al. Contribution of first- versus second-generation products to secondary organic aerosols formed in the oxidation of biogenic hydrocarbons. Environ. Sci. Technol. 40, 2283–2297 (2006).

    CAS  Google Scholar 

  35. Witkowski, B., Al-Sharafi, M., Blaziak, K. & Gierczak, T. Aging of alpha-pinene secondary organic aerosol by hydroxyl radicals in the aqueous phase: kinetics and products. Environ. Sci. Technol. 57, 6040–6051 (2023).

    CAS  Google Scholar 

  36. Marais, E. A. et al. Aqueous-phase mechanism for secondary organic aerosol formation from isoprene: application to the southeast United States and co-benefit of SO2 emission controls. Atmos. Chem. Phys. 16, 1603–1618 (2016).

    CAS  Google Scholar 

  37. Knote, C. et al. Simulation of semi-explicit mechanisms of SOA formation from glyoxal in aerosol in a 3-D model. Atmos. Chem. Phys. 14, 6213–6239 (2014).

    Google Scholar 

  38. Shen, X., Zhao, Y., Chen, Z. & Huang, D. Heterogeneous reactions of volatile organic compounds in the atmosphere. Atmos. Environ. 68, 297–314 (2013).

    CAS  Google Scholar 

  39. Lin, Y. H. et al. Isoprene epoxydiols as precursors to secondary organic aerosol formation: acid-catalyzed reactive uptake studies with authentic compounds. Environ. Sci. Technol. 46, 250–258 (2012).

    CAS  Google Scholar 

  40. Kroll, J. H., Ng, N. L., Murphy, S. M., Flagan, R. C. & Seinfeld, J. H. Secondary organic aerosol formation from isoprene photooxidation. Environ. Sci. Technol. 40, 1869–1877 (2006).

    CAS  Google Scholar 

  41. Kroll, J. H. & Seinfeld, J. H. Chemistry of secondary organic aerosol: formation and evolution of low-volatility organics in the atmosphere. Atmos. Environ. 42, 3593–3624 (2008).

    CAS  Google Scholar 

  42. Ng, N. L. et al. Secondary organic aerosol formation from m-xylene, toluene, and benzene. Atmos. Chem. Phys. 7, 3909–3922 (2007).

    CAS  Google Scholar 

  43. Wang, N., Jorga, S. D., Pierce, J. R., Donahue, N. M. & Pandis, S. N. Particle wall-loss correction methods in smog chamber experiments. Atmos. Meas. Tech. 11, 6577–6588 (2018).

    CAS  Google Scholar 

  44. Zhang, X. et al. Influence of vapor wall loss in laboratory chambers on yields of secondary organic aerosol. Proc. Natl Acad. Sci. USA 111, 5802–5807 (2014).

    CAS  Google Scholar 

  45. Weseley, M. L. Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models. Atmos. Environ. 23, 1293–1304 (1989).

    Google Scholar 

  46. Estimation Programs Interface Suite for Microsoft Windows v.4.1 (EPA, 2015).

  47. Kwok, E. S. C. & Atkinson, R. Estimation of hydroxyl radical reaction rate constants for gas-phase organic compounds using a structure-reactivity relationship: an update. Atmos. Environ. 29, 1685–1695 (1995).

    CAS  Google Scholar 

  48. D’Ambro, E. L. et al. Isomerization of second-generation isoprene peroxy radicals: epoxide formation and implications for secondary organic aerosol yields. Environ. Sci. Technol. 51, 4978–4987 (2017).

    Google Scholar 

  49. Topping, D. et al. UManSysProp v1.0: an online and open-source facility for molecular property prediction and atmospheric aerosol calculations. Geosci. Model Dev. 9, 899–914 (2016).

    Google Scholar 

  50. Heald, C. L. et al. Contrasting reactive organic carbon observations in the southeast United States (SOAS) and Southern California (CalNex). Environ. Sci. Technol. 54, 14923–14935 (2020).

    CAS  Google Scholar 

  51. Chhabra P. S. et al. Application of high-resolution time-of-flight chemical ionization mass spectrometry measurements to estimate volatility distributions of α-pinene and naphthalene oxidation products. Atmos. Meas. Tech. 8, 1–18 (2015).

Download references

Acknowledgements

We appreciate J. Kroll for useful comments that improved this paper and thank B. Murphy, H. Pye, J. Bash and H. Foroutan for valuable scientific discussions on this topic. This work was supported by the Department of Energy Office of Biological and Environmental Research (DE-SC0022020, supporting G.I-V.W. and C.B.) and the National Science Foundation Atmospheric and Geospace Sciences CAREER programme (AGS-2046367, supporting G.I-V.W.).

Author information

Author notes

  1. Chenyang Bi

    Present address: Aerodyne Research Inc., Billerica, MA, USA

  2. These authors contributed equally: Chenyang Bi, Gabriel Isaacman-VanWertz.

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA

    Chenyang Bi & Gabriel Isaacman-VanWertz

Authors
  1. Chenyang Bi
    View author publications

    Search author on:PubMed Google Scholar

  2. Gabriel Isaacman-VanWertz
    View author publications

    Search author on:PubMed Google Scholar

Contributions

C.B. and G.I.-V.W. contributed equally to this work. C.B. performed data analysis and led model implementations and interpretation. G.I.-V.W. conceived the study, contributed to data analysis and conducted modelling. Both authors contributed substantially to writing and editing.

Corresponding author

Correspondence to Gabriel Isaacman-VanWertz.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Geoscience thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Tom Richardson, in collaboration with the Nature Geoscience team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Sensitivity analysis of the deposition timescales to leaf area index (LAI).

Deposition timescale versus oxidation timescale for chemical species in F0AM is shown for a) LAI = 4.7 and b) LAI = 0.47. Markers are sized by relative concentration without deposition and colored by the normalized loss of concentration with and without the implementation of deposition (that is, Δconcentration(Dep-NoDep)/concentration(NoDep)) for simulated precursors and oxidants in the SOAS campaign at 3 hours of the simulation. The impact of transport to the free troposphere is not included here.

Source data

Extended Data Fig. 2 Impact of deposition on modeled oxidation by OH radicals.

Organic aerosol formation and product OH reactivity with and without deposition in modeled OH oxidation by in chemically explicit ‘precursor-oxidant’ cases of a) isoprene-OH, b) benzene-OH, c) toluene-OH, and d) limonene-OH oxidation reactions. The initial concentrations of precursors were set at 1 ppb and the OH concentrations were held at 1 × 106 molecules cm−3. Models with deposition are dashed lines (orange: OH reactivity; blue: total OA) and without deposition are solid lines.

Extended Data Fig. 3 Impact of deposition on modeled oxidation by ozone.

Organic aerosol formation and product OH reactivity with and without deposition in modeled ozone oxidation in chemically explicit ‘precursor-oxidant’ cases of a) isoprene-O3, b) benzene-O3, c) toluene-O3, and d) limonene-O3 oxidation reactions. The initial concentrations of precursors were set at 1 ppb and the O3 concentrations were held at 60 ppb. Models with deposition are dashed lines (orange: OH reactivity; blue: total OA) and without deposition are solid lines.

Extended Data Fig. 4 Impact of deposition on modeled aerosol composition.

Concentrations of the top five dominant aerosol-phase species in the simulation of the α-pinene and OH system (a) without the implementation of deposition and (b) with deposition implemented.

Extended Data Fig. 5 Impact of deposition as a function of product generation.

Ratio of concentration of a species in model runs including vs. not including deposition, with compounds categorized by oxidation generation. Loss of (a) gas-phase species and (b) particle-phase species via deposition. Dots represent chemical species simulated in F0AM at 48 hours (that is, end of simulation) for the α-pinene + OH oxidation reactions. The width of the violin at a given level is proportional to the aggregated relative abundance of chemicals near that level.

Extended Data Fig. 6 Comparison of deposition to wall loss in modeled oxidation chamber experiments.

Modeled organic aerosol formation using the SimpleSOM model33 under the a) ‘oxidation only’ condition where 45 ppb α-pinene was oxidized by OH = 2 × 106 molecules cm−3 with deposition and vapor wall loss turned off; b) ‘oxidation only’ condition with deposition implemented; c) ‘oxidation only’ condition with default vapor wall loss rate in SimpleSOM; and d) ‘oxidation only’ condition with a factor of ten higher default vapor wall loss rate.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–5 and Discussion.

Supplementary Data 1

Deposition lifetimes of all compounds used for chemically explicit modelling, assuming both leaf area index = 4.7 and leaf area index = 0.47. Data used for all chemically explicit modelling to generate main figures and extended data figures.

Source data

Source Data Fig. 2

Raw data for data points shown.

Source Data Extended Data Fig. 1

Raw data for data points shown.

Source Data Extended Data Fig. 6

Raw data for data shown.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bi, C., Isaacman-VanWertz, G. Formation of late-generation atmospheric compounds inhibited by rapid deposition. Nat. Geosci. 18, 213–218 (2025). https://doi.org/10.1038/s41561-025-01650-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41561-025-01650-2

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing