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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Measurement data for the analyses and figures in this study are archived on the Zenodo repository (https://doi.org/10.5281/zenodo.4022816). The FLEXPART-WRF model simulation results are also archived on the Zenodo repository (https://zenodo.org/record/4065107#.X4ajCdD7SUk). Source data are provided with this paper.
The WRF model code is publicly available, has a digital object identifier https://doi.org/10.5065/D6MK6B4K and can be obtained via github (https://github.com/wrf-model/WRF). The FLEXPART-WRF model code is publicly available and can be obtained from https://www.flexpart.eu/wiki/FpLimitedarea. The code for data processing is available upon request from the corresponding author.
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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.
The authors declare no competing interests.
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 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
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
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
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
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
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
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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). https://doi.org/10.1038/s41561-020-00661-5