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Secondary organic aerosol formed by condensing anthropogenic vapours over China’s megacities

Abstract

Secondary organic aerosol contributes a significant fraction to aerosol mass and toxicity. Low-volatility organic vapours are critical intermediates connecting the oxidation of volatile organic compounds to secondary organic aerosol formation. However, the direct measurement of intermediate vapours poses a great challenge. Here we present coordinated measurements of oxygenated organic molecules in the three most urbanized regions of China and determine their likely precursors, enabling us to connect secondary organic aerosol formation to various volatile organic compounds. We show that the oxidation of anthropogenic volatile organic compounds dominates oxygenated organic molecule formation, with an approximately 40% contribution from aromatics and a 40% contribution from aliphatic hydrocarbons (predominantly alkanes), a previously under-accounted class of volatile organic compounds. The irreversible condensation of these anthropogenic oxygenated organic molecules increases significantly in highly polluted conditions, accounting for a major fraction of the production of secondary organic aerosol. We find that the distribution of oxygenated organic molecules and their formation pathways are largely the same across the urbanized regions. This suggests that uniform mitigation strategies could be effective in solving air pollution issues across these highly populated city clusters.

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Fig. 1: Distribution of OOMs in Beijing, Nanjing, Shanghai and Hong Kong.
Fig. 2: Characteristics of aliphatic-OOMs (left) and aromatic-OOMs (right) in Nanjing.
Fig. 3: Factors influencing on OOM formation and the subsequent impact on PM2.5 pollution.
Fig. 4: Contribution of OOMs to SOA.

Data availability

The observation data that support the main findings of this study are available at figshare (https://doi.org/10.6084/m9.figshare.14526801.v1). The aerosol optical depth data used in this work are archived at https://atmosphere-imager.gsfc.nasa.gov/products/monthly. Source data are provided with this paper.

Code availability

Data processing techniques are available on request from the corresponding author.

References

  1. IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  2. Heal, M. R., Kumar, P. & Harrison, R. M. Particles, air quality, policy and health. Chem. Soc. Rev. 41, 6606–6630 (2012).

    Google Scholar 

  3. Jimenez, J. L. et al. Evolution of organic aerosols in the atmosphere. Science 326, 1525–1529 (2009).

    Google Scholar 

  4. Huang, R. J. et al. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514, 218–222 (2014).

    Google Scholar 

  5. Zhou, J. et al. Predominance of secondary organic aerosol to particle-bound reactive oxygen species activity in fine ambient aerosol. Atmos. Chem. Phys. 19, 14703–14720 (2019).

    Google Scholar 

  6. Laskin, A., Laskin, J. & Nizkorodov, S. Mass spectrometric approaches for chemical characterisation of atmospheric aerosols: critical review of the most recent advances. Environ. Chem. 9, 163–189 (2012).

    Google Scholar 

  7. Nozière, B. et al. The molecular identification of organic compounds in the atmosphere: state of the art and challenges. Chem. Rev. 115, 3919–3983 (2015).

    Google Scholar 

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

    Google Scholar 

  9. Yan, C. et al. Source characterization of highly oxidized multifunctional compounds in a boreal forest environment using positive matrix factorization. Atmos. Chem. Phys. 16, 12715–12731 (2016).

    Google Scholar 

  10. Zhang, Y. et al. Insights into atmospheric oxidation processes by performing factor analyses on subranges of mass spectra. Atmos. Chem. Phys. 20, 5945–5961 (2020).

    Google Scholar 

  11. Ehn, M. et al. A large source of low-volatility secondary organic aerosol. Nature 506, 476–479 (2014).

    Google Scholar 

  12. Troestl, J. et al. The role of low-volatility organic compounds in initial particle growth in the atmosphere. Nature 533, 527–531 (2016).

    Google Scholar 

  13. Kürten, A., Rondo, L., Ehrhart, S. & Curtius, J. Calibration of a chemical ionization mass spectrometer for the measurement of gaseous sulfuric acid. J. Phys. Chem. A 116, 6375–6386 (2012).

    Google Scholar 

  14. Heinritzi, M. et al. Characterization of the mass-dependent transmission efficiency of a CIMS. Atmos. Meas. Tech. 9, 1449–1460 (2016).

    Google Scholar 

  15. Zhang, Y. et al. A novel approach for simple statistical analysis of high-resolution mass spectra. Atmos. Meas. Tech. 12, 3761–3776 (2019).

    Google Scholar 

  16. Liu, Y. et al. Formation of condensable organic vapors from anthropogenic and biogenic volatile organic compounds (VOCs) is strongly perturbed by NOx in eastern China. Atmos. Chem. Phys. 21, 14789–14814 (2021).

    Google Scholar 

  17. Xu, Z. N. et al. Multifunctional products of isoprene oxidation in polluted atmosphere and their contribution to SOA. Geophys. Res. Lett. 48, e2020GL089276 (2021).

    Google Scholar 

  18. Bianchi, F. et al. Highly oxygenated organic molecules (HOM) from gas-phase autoxidation involving peroxy radicals: a key contributor to atmospheric aerosol. Chem. Rev. 119, 3472–3509 (2019).

    Google Scholar 

  19. Wang, M. et al. Photo-oxidation of aromatic hydrocarbons produces low-volatility organic compounds. Environ. Sci. Technol. 54, 7911–7921 (2020).

    Google Scholar 

  20. Dang, C. et al. The effect of structure and isomerism on the vapor pressures of organic molecules and its potential atmospheric relevance. Aerosol Sci. Tech. 53, 1040–1055 (2019).

    Google Scholar 

  21. Cheng, X. et al. Secondary production of gaseous nitrated phenols in polluted urban environments. Environ. Sci. Technol. 55, 4410–4419 (2021).

    Google Scholar 

  22. Wang, Z., Zhang, J., Zhang, L., Liang, Y. & Shi, Q. Characterization of nitroaromatic compounds in atmospheric particulate matter from Beijing. Atmos. Environ. 246, 118046 (2021).

    Google Scholar 

  23. Wang, Z. et al. Efficient alkane oxidation under combustion engine and atmospheric conditions. Commun. Chem. 4, 18 (2021).

    Google Scholar 

  24. Molteni, U. et al. Formation of highly oxygenated organic molecules from aromatic compounds. Atmos. Chem. Phys. 18, 1909–1921 (2018).

    Google Scholar 

  25. Garmash, O. et al. Multi-generation OH oxidation as a source for highly oxygenated organic molecules from aromatics. Atmos. Chem. Phys. 20, 515–537 (2020).

    Google Scholar 

  26. Wang, Y. et al. Oxygenated products formed from OH-initiated reactions of trimethylbenzene: autoxidation and accretion. Atmos. Chem. Phys. 20, 9563–9579 (2020).

    Google Scholar 

  27. Simon, M. et al. Molecular understanding of new-particle formation from α-pinene between −50 and +25 °C. Atmos. Chem. Phys. 20, 9183–9207 (2020).

    Google Scholar 

  28. Wang, S., Wu, R., Berndt, T., Ehn, M. & Wang, L. Formation of highly oxidized radicals and multifunctional products from the atmospheric oxidation of alkylbenzenes. Environ. Sci. Technol. 51, 8442–8449 (2017).

    Google Scholar 

  29. Mehra, A. et al. Evaluation of the chemical composition of gas- and particle-phase products of aromatic oxidation. Atmos. Chem. Phys. 20, 9783–9803 (2020).

    Google Scholar 

  30. 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).

    Google Scholar 

  31. Wang, L., Wu, R. & Xu, C. Atmospheric oxidation mechanism of benzene. Fates of alkoxy radical intermediates and revised mechanism. J. Phys. Chem. A 117, 14163–14168 (2013).

    Google Scholar 

  32. Pankow, J. F. & Asher, W. E. SIMPOL.1: a simple group contribution method for predicting vapor pressures and enthalpies of vaporization of multifunctional organic compounds. Atmos. Chem. Phys. 8, 2773–2796 (2008).

    Google Scholar 

  33. Mohr, C. et al. Molecular identification of organic vapors driving atmospheric nanoparticle growth. Nat. Commun. 10, 4442 (2019).

    Google Scholar 

  34. Li, Y., Pöschl, U. & Shiraiwa, M. Molecular corridors and parameterizations of volatility in the chemical evolution of organic aerosols. Atmos. Chem. Phys. 16, 3327–3344 (2016).

    Google Scholar 

  35. Tan, Z. et al. Wintertime photochemistry in Beijing: observations of ROx radical concentrations in the North China Plain during the BEST-ONE campaign. Atmos. Chem. Phys. 18, 12391–12411 (2018).

    Google Scholar 

  36. Lu, K. et al. Fast photochemistry in wintertime haze: consequences for pollution mitigation strategies. Environ. Sci. Technol. 53, 10676–10684 (2019).

    Google Scholar 

  37. Duan, J. et al. Summertime and wintertime atmospheric processes of secondary aerosol in Beijing. Atmos. Chem. Phys. 20, 3793–3807 (2020).

    Google Scholar 

  38. Huang, X. et al. Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China. Natl Sci. Rev. 8, nwaa137 (2021).

    Google Scholar 

  39. Tilmes, S. et al. Climate forcing and trends of organic aerosols in the Community Earth System Model (CESM2). J. Adv. Model. Earth Syst. 11, 4323–4351 (2019).

    Google Scholar 

  40. Zhang, F. et al. An unexpected catalyst dominates formation and radiative forcing of regional haze. Proc. Natl Acad. Sci. USA 117, 3960–3966 (2020).

    Google Scholar 

  41. Huang, X. et al. Amplified transboundary transport of haze by aerosol-boundary layer interaction in China. Nat. Geosci. 13, 428–434 (2020).

    Google Scholar 

  42. 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).

    Google Scholar 

  43. Kulmala, M. et al. Opinion: Gigacity—a source of problems or the new way to sustainable development. Atmos. Chem. Phys. 21, 8313–8322 (2021).

    Google Scholar 

  44. Odum, J. R. et al. Gas/particle partitioning and secondary organic aerosol yields. Environ. Sci. Technol. 30, 2580–2585 (1996).

    Google Scholar 

  45. Cocker, D. R. III., Mader, B. T., Kalberer, M., Flagan, R. C. & Seinfeld, J. H. The effect of water on gas-particle partitioning of secondary organic aerosol: II. m-xylene and 1,3,5-trimethylbenzene photooxidation systems. Atmos. Environ. 35, 6073–6085 (2001).

    Google Scholar 

  46. Song, C., Na, K. & Cocker, D. R. Impact of the hydrocarbon to NOx ratio on secondary organic aerosol formation. Environ. Sci. Technol. 39, 3143–3149 (2005).

    Google Scholar 

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

    Google Scholar 

  48. Sato, K. et al. AMS and LC/MS analyses of SOA from the photooxidation of benzene and 1,3,5-trimethylbenzene in the presence of NOx: effects of chemical structure on SOA aging. Atmos. Chem. Phys. 12, 4667–4682 (2012).

    Google Scholar 

  49. Li, L., Tang, P., Nakao, S., Chen, C. L. & Cocker, D. R. III. Role of methyl group number on SOA formation from monocyclic aromatic hydrocarbons photooxidation under low-NOx conditions. Atmos. Chem. Phys. 16, 2255–2272 (2016).

    Google Scholar 

  50. Li, L., Tang, P., Nakao, S. & Cocker, D. R. III. Impact of molecular structure on secondary organic aerosol formation from aromatic hydrocarbon photooxidation under low-NOx conditions. Atmos. Chem. Phys. 16, 10793–10808 (2016).

    Google Scholar 

  51. Breitenlechner, M. et al. PTR3: an instrument for studying the lifecycle of reactive organic carbon in the atmosphere. Anal. Chem. 89, 5824–5831 (2017).

    Google Scholar 

  52. Hyttinen, N. et al. Modeling the charging of highly oxidized cyclohexene ozonolysis products using nitrate-based chemical ionization. J. Phys. Chem. A 119, 6339–6345 (2015).

    Google Scholar 

  53. Hyttinen, N. et al. Computational comparison of different reagent ions in the chemical ionization of oxidized multifunctional compounds. J. Phys. Chem. A 122, 269–279 (2018).

    Google Scholar 

  54. Riva, M. et al. Evaluating the performance of five different chemical ionization techniques for detecting gaseous oxygenated organic species. Atmos. Meas. Tech. 12, 2403–2421 (2019).

    Google Scholar 

  55. Kawamura, K. & Bikkina, S. A review of dicarboxylic acids and related compounds in atmospheric aerosols: molecular distributions, sources and transformation. Atmos. Res. 170, 140–160 (2016).

    Google Scholar 

  56. Elm, J., Hyttinen, N., Lin, J. J., Kurtén, T. & Prisle, N. L. Strong even/odd pattern in the computed gas-phase stability of dicarboxylic acid dimers: implications for condensation thermodynamics. J. Phys. Chem. A 123, 9594–9599 (2019).

    Google Scholar 

  57. Donahue, N. M., Robinson, A. L., Stanier, C. O. & Pandis, S. N. Coupled partitioning, dilution, and chemical aging of semivolatile organics. Environ. Sci. Technol. 40, 2635–2643 (2006).

    Google Scholar 

  58. Yang, L. et al. Toward building a physical proxy for gas-phase sulfuric acid concentration based on its budget analysis in polluted Yangtze River Delta, East China. Environ. Sci. Technol. 55, 6665–6676 (2021).

    Google Scholar 

  59. Seinfeld, J. H. & Pandis, S. N. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change (Wiley, 2016).

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) project (92044301, 41875175, 42075101, 21806108, 91744204 and 22188102), the Jiangsu Provincial Collaborative Innovation Center of Climate Change, Samsung PM2.5 SRP, the Research Grants Council of Hong Kong Special Administrative Region (grants nos. T24/504/17-N and 15265516), the Shanghai Rising-Star Program (19QB1402900) and the US National Science Foundation (AGS1801897). K.R.D. acknowledges support by the Swiss National Science Foundation mobility grant P2EZP2_181599. We thank Y. Liu for processing aerosol optical depth data. The Hong Kong team would like to acknowledge the HKPolyU University Research Facility in Chemical and Environmental Analysis (UCEA) for equipment support, and the Hong Kong Environmental Protection Department for providing access to the team to conduct measurements at Cape D’Aguilar Supersite AQMS and for sharing the trace gas, PM2.5 and VOCs data at the Supersite.

Author information

Authors and Affiliations

Authors

Contributions

W.N., C. Yan, D.D.H., Z.W., A.D., J.J. and M.K. designed the study. W.N., C. Yan, D.D.H., Z.W., Yuliang Liu, X. Qiao, Y.G., L.T. and P.Z. analysed the data. W.N., C. Yan, D.D.H., Z.W., A.D., J.J., M.E. and N.M.D. wrote the manuscript. Yuliang Liu, Zhengning Xu, Y. Li, X. Qiao, Y.G. and P.Z. collected other research materials. All authors participated in relevant scientific discussion and commented on the manuscript.

Corresponding authors

Correspondence to Jingkun Jiang or Aijun Ding.

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Nature Geoscience thanks Jacqueline Hamilton, Ru-Jin Huang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Xujia Jiang and Tom Richardson, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Time series of observed OOMs and related parameters in (a) Beijing, (b) Nanjing, (c) Shanghai, and (d) Hong Kong.

Variables include UVB (JO1D in Shanghai), Temperature, RH, NOx, O3, primary organic aerosol (POA), secondary organic aerosol (SOA), total OOMs and nitrophenols.

Extended Data Fig. 2 Correlation of OOMs measured by nitrate- and iodide- CIMS (A-F), C5-10 CHO OOMs with different number of oxygen (G) C5-10 CHO OOMs and (H) C5-10 CHON OOMs in Beijing.

Time period of data is from 1st to 28th January 2020. The numbers in the brackets are the corresponding number of common species that can be detected by both instruments. R denotes the person correlation coefficient.

Extended Data Fig. 3 Overview of the PMF results.

(a) comparison of PMF results from the four different cities; (b) an example of one of the common factors: profile and diurnal variation of common factor 6 (night-time monoterpene factor). The dark yellow dots in the diurnal plot represent the mean value; the line and the shaded area represent 50th percentile and 25th−75th percentile, respectively. (c) mass defect plot of common factor 6 in Nanjing.

Extended Data Fig. 4 A decision-tree based workflow.

A decision-tree based workflow to identify the precursors of detected OOM.

Extended Data Fig. 5 The accuracy of workflow tested by known OOM peak lists of (a) Nitrate-CIMS and (b) I-CIMS from laboratory experiments.

Superscripts 1, 2, 3 in panel (a) refer to (1) Molteni et al., 2018, (2) Garmash et al., 2020, and (3) Wang et al., 2021. There are 4 different experiments for the oxidation of benzene: (*) Experiment in a flow reactor, (**) Experiment with low OH/VOC in the JPAC chamber, (***) Experiment with high OH/VOC in the JPAC chamber, and (****) Experiment affected by NOx in the JPAC chamber. Peak lists used in panel (b) are from Mehra et al., 2020.

Extended Data Fig. 6 The distributions of the total observed OOMs (upper panel), aliphatic-OOMs (middle panel) and aromatic-OOMs (lower panel) grouped by (a) the numbers of carbon (nC), (b) effective oxygen (nO-eff), (c) nitrogen (nN) and (d) double bond equivalent (DBE) in four different cities.

Columns in blue, green, orange and purple represent Beijing, Nanjing, Shanghai and Hong Kong, respectively.

Extended Data Fig. 7 Volatility distribution of observed OOMs in 4 megacities at (a) observed actual temperature, and (b) 300 K.

Columns in blue, green, orange and purple represent Beijing, Nanjing, Shanghai and Hong Kong, respectively.

Extended Data Fig. 8 OOMs condensation flux as a dependent of PM2.5 in (a) Beijing, (b) Nanjing, (c) Shanghai, and (d) Hong Kong.

Aliphatic-OOMs in red, aromatic-OOMs in blue, isoprene-OOMs in bright yellow, monoterpene-OOMs in dark yellow and undistinguished OOMs in grey.

Extended Data Fig. 9 Correlation between detected OOMs from different precursor classes and PM2.5 in Beijing, Nanjing, Shanghai and Hong Kong.

Aliphatic-OOMs in red, aromatic-OOMs in blue, isoprene-OOMs in bright yellow, monoterpene-OOMs in dark yellow and undistinguished OOMs in grey.

Extended Data Fig. 10 Case showing the selection of SOA formation episode.

A stable weather condition is critical for selecting SOA formation episodes to exclude the influence of air mass changes. Four parameters, including wind speed, wind direction, boundary layer height and water concentrations, are used for the judgement. For one sampling period, when these four parameters kept stable, it can be identified as a SOA episode. These selected SOA episodes mostly concentrated around noontime or night-time time when the boundary layer was stable. In total, 16 episodes in Beijing, 19 episodes in Nanjing, 8 episodes in Shanghai, and 18 episodes in Hong Kong were selected for further analysis. We also test the potential uncertainties from case selection by varying the start- and end-point of the case. Cases with the uncertainties of d(SOA)/dt higher than 30% are excluded.

Supplementary information

Supplementary Information

Supplementary information of sampling sites and measurements, Figs. 1–3 and Tables 1–3.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Molecular composition data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

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Nie, W., Yan, C., Huang, D.D. et al. Secondary organic aerosol formed by condensing anthropogenic vapours over China’s megacities. Nat. Geosci. 15, 255–261 (2022). https://doi.org/10.1038/s41561-022-00922-5

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