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Biogenic particles formed in the Himalaya as an important source of free tropospheric aerosols


Aerosols of biogenic and anthropogenic origin affect the total radiative forcing of global climate. Poor knowledge of the pre-industrial aerosol concentration and composition, in particular of particles formed directly in the atmosphere from gaseous precursors, constitutes a large uncertainty in the anthropogenic radiative forcing. Investigations of new particle formation at pre-industrial-like conditions can contribute to the reduction of this uncertainty. Here we present observations taken at the remote Nepal Climate Observatory Pyramid station at 5,079 m above sea level, a few kilometres from the summit of Everest. We show that up-valley winds funnel gaseous aerosol precursors to higher altitudes. During this transport, these are oxidized into compounds of very low volatility, which rapidly form a large number of aerosol particles. These are then transported into the free troposphere, which suggests that the whole Himalayan region may act as an ‘aerosol factory’ and contribute substantially to the free tropospheric aerosol population. Aerosol production in this region occurs mainly via organic precursors of biogenic origin with little evidence of the involvement of anthropogenic pollutants. This process is therefore likely to be essentially unchanged since the pre-industrial period, and may have been one of the major sources that contributes to the upper tropospheric aerosol population during that time.

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Fig. 1: Size distribution of aerosol particles observed at the NCO-P station.
Fig. 2: Influence of wind direction on the diurnal variation of ion cluster and particle concentrations.
Fig. 3: Chemical composition of the positive and negative ions (molecules and clusters) during NPF events.
Fig. 4: Diurnal evolution of positive and negative ions, a sulfuric acid proxy and concentration of recently formed particles.
Fig. 5: FLEXPART-WRF simulation of the transport of passive tracers released at the Pyramid station.

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Data availability

Measurement data for the analyses and figures in this study are archived on the Zenodo repository ( The FLEXPART-WRF model simulation results are also archived on the Zenodo repository ( Source data are provided with this paper.

Code availability

The WRF model code is publicly available, has a digital object identifier and can be obtained via github ( The FLEXPART-WRF model code is publicly available and can be obtained from The code for data processing is available upon request from the corresponding author.


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

  2. Dunne, E. M. et al. Global atmospheric particle formation from CERN CLOUD measurements. Science 354, 1119–1124 (2016).

    Article  Google Scholar 

  3. Gordon, H. et al. Causes and importance of new particle formation in the present-day and preindustrial atmospheres. J. Geophys. Res. Atmos. 122, 8739–8760 (2017).

    Article  Google Scholar 

  4. Merikanto, J., Spracklen, D. V., Mann, G. W., Pickering, S. J. & Carslaw, K. S. Impact of nucleation on global CCN. Atmos. Chem. Phys. 9, 8601–8616 (2009).

    Article  Google Scholar 

  5. Kirkby, J. et al. Ion-induced nucleation of pure biogenic particles. Nature 533, 521–526 (2016).

    Article  Google Scholar 

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

    Article  Google Scholar 

  7. Bianchi, F. et al. New particle formation in the free troposphere: a question of chemistry and timing. Science 352, 1109–1112 (2016).

    Article  Google Scholar 

  8. Sellegri, K. et al. Seasonal variations of aerosol size distributions based on long-term measurements at the high altitude Himalayan site of Nepal Climate Observatory-Pyramid (5079 m), Nepal. Atmos. Chem. Phys. 10, 10679–10690 (2010).

    Article  Google Scholar 

  9. Venzac, H. et al. High frequency new particle formation in the Himalayas. Proc. Natl Acad. Sci. USA 105, 15666–15671 (2008).

    Article  Google Scholar 

  10. Bonasoni, P. et al. Atmospheric brown clouds in the Himalayas: first two years of continuous observations at the Nepal Climate Observatory-Pyramid (5079 m). Atmos. Chem. Phys. 10, 7515–7531 (2010).

    Article  Google Scholar 

  11. Marinoni, A. et al. Aerosol mass and black carbon concentrations, a two year record at NCO-P (5079 m, Southern Himalayas). Atmos. Chem. Phys. 10, 8551–8562 (2010).

    Article  Google Scholar 

  12. 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).

    Article  Google Scholar 

  13. Bianchi, F. et al. The role of highly oxygenated molecules (HOMs) in determining the composition of ambient ions in the boreal forest. Atmos. Chem. Phys. 17, 13819–13831 (2017).

    Article  Google Scholar 

  14. Ehn, M. et al. Composition and temporal behavior of ambient ions in the boreal forest. Atmos. Chem. Phys. 10, 8513–8530 (2010).

    Article  Google Scholar 

  15. Almeida, J. et al. Molecular understanding of sulphuric acid–amine particle nucleation in the atmosphere. Nature 502, 359–363 (2013).

    Article  Google Scholar 

  16. Kirkby, J. et al. Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation. Nature 476, 429–433 (2011).

    Article  Google Scholar 

  17. Bajracharya, B., Uddin, K., Chettri, N., Shrestha, B. & Siddiqui, S. A. Understanding land cover change using a harmonized classification system in the Himalaya. Mt. Res. Dev. 30, 143–156 (2010).

    Article  Google Scholar 

  18. Guenther, A. et al. A global model of natural volatile organic compound emissions. J. Geophys. Res. Atmos. 100, 8873–8892 (1995).

    Article  Google Scholar 

  19. Skamarock, W. C. et al. A Description of the Advanced Research WRF Version 3 (National Center for Atmospheric Research, 2008).

  20. Brioude, J. et al. The Lagrangian particle dispersion model FLEXPART-WRF version 3.1. Geosci. Model Dev. 6, 1889–1904 (2013).

    Article  Google Scholar 

  21. De Wekker, S. F. J. & Kossmann, M. Convective boundary layer heights over mountainous terrain—a review of concepts. Front. Earth Sci. 3, 77 (2015).

    Article  Google Scholar 

  22. Henne, S. et al. Quantification of topographic venting of boundary layer air to the free troposphere. Atmos. Chem. Phys. 4, 497–509 (2004).

    Article  Google Scholar 

  23. Nyeki, S. et al. Airborne lidar and in-situ aerosol observations of an elevated layer, leeward of the European Alps and Apennines. Geophys. Res. Lett. 29, 1852 (2002).

    Article  Google Scholar 

  24. WMO/GAW Aerosol Measurement Procedures, Guidelines and Recommendations 2nd edn (World Meteorological Organization, 2016).

  25. Marinoni, A. et al. High black carbon and ozone concentrations during pollution transport in the Himalayas: five years of continuous observations at NCO-P global GAW station. J. Environ. Sci. 25, 1618–1625 (2013).

    Article  Google Scholar 

  26. Vanhanen, J. et al. Particle size magnifier for nano-CN detection. Aerosol Sci. Tech. 45, 533–542 (2011).

    Article  Google Scholar 

  27. Kangasluoma, J. et al. Characterization of a Herrmann-type high-resolution differential mobility analyzer. Aerosol Sci. Tech. 50, 222–229 (2016).

    Article  Google Scholar 

  28. Lehtipalo, K. et al. Methods for determining particle size distribution and growth rates between 1 and 3 nm using the Particle Size Magnifier. Boreal Environ. Res. 19, 215–236 (2014).

    Google Scholar 

  29. Rose, C. et al. Major contribution of neutral clusters to new particle formation at the interface between the boundary layer and the free troposphere. Atmos. Chem. Phys. 15, 3413–3428 (2015).

    Article  Google Scholar 

  30. Manninen, H. E., Mirme, S., Mirme, A., Petäjä, T. & Kulmala, M. How to reliably detect molecular clusters and nucleation mode particles with neutral cluster and air ion spectrometer (NAIS). Atmos. Meas. Tech. 9, 3577–3605 (2016).

    Article  Google Scholar 

  31. Mirme, S. & Mirme, A. The mathematical principles and design of the NAIS—a spectrometer for the measurement of cluster ion and nanometer aerosol size distributions. Atmos. Meas. Tech. 6, 1061–1071 (2013).

    Article  Google Scholar 

  32. Wagner, R. et al. On the accuracy of ion measurements using a neutral cluster and air ion spectrometer. Boreal Environ. Res. 21, 230–241 (2016).

    Google Scholar 

  33. Junninen, H. et al. A high-resolution mass spectrometer to measure atmospheric ion composition. Atmos. Meas. Tech. 3, 1039–1053 (2010).

    Article  Google Scholar 

  34. Jokinen, T. et al. Atmospheric sulphuric acid and neutral cluster measurements using CI-APi-TOF. Atmos. Chem. Phys. 12, 4117–4125 (2012).

    Article  Google Scholar 

  35. Saha, S. et al. The NCEP climate forecast system reanalysis. Bull. Am. Meteorol. Soc. 91, 1015–1058 (2010).

    Article  Google Scholar 

  36. Stohl, A., Forster, C., Frank, A., Seibert, P. & Wotawa, G. Technical note: the Lagrangian particle dispersion model FLEXPART version 6.2. Atmos. Chem. Phys. 5, 2461–2474 (2005).

    Article  Google Scholar 

  37. Vogelezang, D. H. P. & Holtslag, A. A. M. Evaluation and model impacts of alternative boundary-layer height formulations. Bound.-Layer Meteorol. 81, 245–269 (1996).

    Article  Google Scholar 

  38. Hanna, S. R. in Atmospheric Turbulence and Air Pollution Modelling Ch. 7 (D. Reidel, 1982).

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The NCO-P observations were carried out in the framework of the EvK2CNR SHARE (Stations at High Altitude for Research on the Environment) project. We thank the Nepalese staff who work at NCO-P for their valuable work under difficult conditions. We also acknowledge the CSC — IT Center for Science, Finland, for generous computational resources that enabled the WRF and FLEXPART-WRF simulations to be conducted. We thank the Swiss National Science Foundation (no. 200020_152907), the INSU CNRS as part of the long-term atmospheric observation programme (CLAP), Labex OSUG@2020 (Investissements d’avenir — ANR10 LABX56), the European Regional Development Fund (project MOBTT42), ACTRIS, the European Research Council (ERC; project CHAPAs no. 850614 and ATM-GTP no. 742206), the Finnish Centre of Excellence as well as the Academy of Finland (project nos 316114, 311932, 315203 and 1315203). We thank the tofTools team for providing the tools for mass spectrometry analysis.

Author information

Authors and Affiliations



F.B. conceived the study and led the overall scientific investigation. F.B. and H.J. organized and conducted the Himalayan expeditions. F.B., H.J., A.B., L.D., Q.Z., L.Y., K.L., J. Kontkanen, A.M., U.M., M.R., C.R. and C.Y. performed the data analysis. V.A.S. performed and analysed the WRF and FLEXPART simulations. F.B., V.A.S., A.B., C.R.H., Q.Z., P.L., K.L., V.M.K., T.P., K.S., D.R.W., M.K., U.B. and J.D. carried out the data interpretation. L.R.A., P.B., M.H., J. Kangasluoma, S.B.M., S.M., A.M. and U.M. helped with logistic challenges, with instrument support and data quality assurance. P.B., P.L., A.M. and K.S. provided the measurement data from the long-term observations. F.B., V.A.S., V.M.K., U.B. and J.D. wrote the manuscript with contributions from all the authors.

Corresponding author

Correspondence to F. Bianchi.

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Competing interests

The authors declare no competing interests.

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Peer review information Primary Handling Editors: Tamara Goldin; Xujia Jiang.

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

Extended data

Extended Data Fig. 1 Ion and particle size distribution observed during the intensive measurement period.

Panels a and b show the size distribution of the negative and positive ions measured by the NAIS. Panel c combines the size distribution of the particles measured by the NAIS (2–40 nm) with the size distribution measured by the PSM (1–2 nm). During these NPF events, the particles grew to the size of several tens of nm.

Source data

Extended Data Fig. 2 Wind direction at the Pyramid station.

Mean hourly wind roses for November and December over the years 2002–2012 at NCO-P.

Source data

Extended Data Fig. 3 Influence of wind direction on the diurnal variation of ion cluster and particle concentrations.

Panel a shows the mean temporal evolutions of negative ions measured by the NAIS and the APi-TOF during all the NPF events where the APi-TOF was measuring in negative mode (see Supplementary Table 1). Data are aggregated by starting time of the NPF event. Panel b shows the temporal evolution of the concentrations for positive ions from the NAIS as well as for selected m/z ranges measured by the APi-TOF during the NPF event detected on 06 December 2014. The grey dashed line indicates the moment when the wind changes direction and new particle formation occurs.

Source data

Extended Data Fig. 4 Box plot of estimated growth rates for different size ranges.

The red line is the median growth rate at different size. Box = 25th and 75th percentiles; Whisker 10th and 90th percentiles.

Source data

Extended Data Fig. 5 Diurnal variations of particles, equivalent black carbon (eBC) and PM1 observed during the measurement period.

Particles (3.2 < d < 6.5 nm) diurnal variation measured by the NAIS is shown in red, eBC is shown in black and PM1 in green. Data was aggregated by defining the last 30 minutes interval before the onset of southerly wind as time zero.

Source data

Extended Data Fig. 6 Polar plots of wind direction.

In both panels the radial axes and the colour shading show the time of day (local time) for a, observations and b, model values averaged to the same 30-minute resolution as the observations. Black dashed lines show the start of the FLEXPART simulation (08:45 local time) and the end of the release (14:45 local time). All 5 days are included in both figures.

Source data

Extended Data Fig. 7 Tracer concentrations on 20 December 2014.

The position of all individual particles is used to calculate a particle concentration (ppt by mass) on the same latitude-longitude grid as the inner-most (highest resolution) WRF meteorological data. Panel a shows gridded concentration at 50 m above local ground level, 1 hour after the release. Panel b shows gridded concentration at 1.5 km above local ground level, 6 hours after the release. The colour code shows the particle concentration on a log10 scale. Topography is shown in solid contours (contour interval 1 km). Black contours show 2 km, purple contours 6 km and magenta contours 7 km a.s.l. The star in panels a and b denotes the location of the Pyramid station and thus where the particles were released from.

Source data

Extended Data Fig. 8 Fraction of passive tracers in the mixed layer.

The percentage of passive tracers that are still within the simulation domain (note that some are advected out of the domain at later times) and are in the mixed layer as defined by FLEXPART using a Richardson number-based approach. Time is hours from the start of the simulations.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–17, Discussion and Tables 1 and 2.

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Bianchi, F., Junninen, H., Bigi, A. et al. Biogenic particles formed in the Himalaya as an important source of free tropospheric aerosols. Nat. Geosci. 14, 4–9 (2021).

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