TY  - JOUR
A1  - Wang, Mingyi
A1  - Xiao, Mao
A1  - Bertozzi, Barbara
A1  - Marie, Guillaume
A1  - Rörup, Birte
A1  - Schulze, Benjamin
A1  - Bardakov, Roman
A1  - He, Xu-Cheng
A1  - Shen, Jiali
A1  - Scholz, Wiebke
A1  - Marten, Ruby
A1  - Dada, Lubna
A1  - Baalbaki, Rima
A1  - Lopez, Brandon
A1  - Lamkaddam, Houssni
A1  - Manninen, Hanna E.
A1  - Amorim, Antonio
A1  - Ataei, Farnoush
A1  - Bogert, Pia
A1  - Brasseur, Zoé
A1  - Caudillo, Lucía
A1  - De Menezes, Louis-Philippe
A1  - Duplissy, Jonathan
A1  - Ekman, Annica M. L.
A1  - Finkenzeller, Henning
A1  - Gonzalez Carracedo, Loïc
A1  - Granzin, Manuel
A1  - Guida, Roberto
A1  - Heinritzi, Martin
A1  - Hofbauer, Victoria
A1  - Höhler, Kristina
A1  - Korhonen, Kimmo
A1  - Krechmer, Jordan E.
A1  - Kürten, Christoph Andreas
A1  - Lehtipalo, Katrianne
A1  - Mahfouz, Naser G. A.
A1  - Makhmutov, Vladimir
A1  - Massabò, Dario
A1  - Mathot, Serge
A1  - Mauldin, Roy L.
A1  - Mentler, Bernhard
A1  - Müller, Tatjana
A1  - Onnela, Antti
A1  - Petäjä, Tuukka
A1  - Philippov, Maxim
A1  - Piedehierro, Ana A.
A1  - Pozzer, Andrea
A1  - Ranjithkumar, Ananth
A1  - Schervish, Meredith
A1  - Schobesberger, Siegfried
A1  - Simon, Mario
A1  - Stozhkov, Yuri
A1  - Tomé, António
A1  - Umo, Nsikanabasi Silas
A1  - Vogel, Franziska
A1  - Wagner, Robert
A1  - Wang, Dongyu S.
A1  - Weber, Stefan K.
A1  - Welti, André
A1  - Wu, Yusheng
A1  - Zauner-Wieczorek, Marcel
A1  - Sipilä, Mikko
A1  - Winkler, Paul M.
A1  - Hansel, Armin
A1  - Baltensperger, Urs
A1  - Kulmala, Markku
A1  - Flagan, Richard C.
A1  - Curtius, Joachim
A1  - Riipinen, Ilona
A1  - Gordon, Hamish
A1  - Lelieveld, Jos
A1  - El Haddad, Imad
A1  - Volkamer, Rainer
A1  - Worsnop, Douglas R.
A1  - Christoudias, Theodoros
A1  - Kirkby, Jasper
A1  - Möhler, Ottmar
A1  - Donahue, Neil McPherson
T1  - Synergistic HNO3–H2SO4–NH3 upper tropospheric particle formation
T2  - Nature
N2  - New particle formation in the upper free troposphere is a major global source of cloud condensation nuclei (CCN)1,2,3,4. However, the precursor vapours that drive the process are not well understood. With experiments performed under upper tropospheric conditions in the CERN CLOUD chamber, we show that nitric acid, sulfuric acid and ammonia form particles synergistically, at rates that are orders of magnitude faster than those from any two of the three components. The importance of this mechanism depends on the availability of ammonia, which was previously thought to be efficiently scavenged by cloud droplets during convection. However, surprisingly high concentrations of ammonia and ammonium nitrate have recently been observed in the upper troposphere over the Asian monsoon region5,6. Once particles have formed, co-condensation of ammonia and abundant nitric acid alone is sufficient to drive rapid growth to CCN sizes with only trace sulfate. Moreover, our measurements show that these CCN are also highly efficient ice nucleating particles—comparable to desert dust. Our model simulations confirm that ammonia is efficiently convected aloft during the Asian monsoon, driving rapid, multi-acid HNO3–H2SO4–NH3 nucleation in the upper troposphere and producing ice nucleating particles that spread across the mid-latitude Northern Hemisphere.
KW  - Atmospheric chemistry
KW  - Atmospheric science
KW  - Climate change
Y1  - 2022
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/63265
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-632653
SN  - 1476-4687
N1  - The full dataset shown in the figures is publicly available at https://doi.org/10.5281/zenodo.5949440
N1  - We thank the European Organization for Nuclear Research (CERN) for supporting CLOUD with important technical and financial resources. This research has received funding from the US National Science Foundation (nos. AGS-1801574, AGS-1801897, AGS-1602086, AGS-1801329, AGS-2132089 and AGS-1801280), the European Union’s Horizon 2020 programme (Marie Skłodowska-Curie ITN no. 764991 ‘CLOUD-MOTION’), the European Commission, H2020 Research Infrastructures (FORCeS, no. 821205), the European Union’s Horizon 2020 research and innovation programme (Marie Skłodowska-Curie no. 895875 ‘NPF-PANDA’), a European Research Council (ERC) project ATM-GTP contract (no. 742206), an ERC-CoG grant INTEGRATE (no. 867599), the Swiss National Science Foundation (nos. 200021_169090, 200020_172602 and 20FI20_172622), the Academy of Finland ACCC Flagship (no. 337549), the Academy of Finland Academy professorship (no. 302958), the Academy of Finland (nos. 1325656, 316114 and 325647), Russian MegaGrant project ‘Megapolis – heat and pollution island: interdisciplinary hydroclimatic, geochemical and ecological analysis’ (application reference 2020-220-08-5835), Jane and Aatos Erkko Foundation ‘Quantifying carbon sink, CarbonSink+ and their interaction with air quality’ INAR project, Samsung PM2.5 SRP, Prince Albert Foundation ‘the Arena for the gap analysis of the existing Arctic Science Co-Operations (AASCO)’ (no. 2859), the German Federal Ministry of Education and Research (CLOUD-16 project nos. 01LK1601A and 01LK1601C), the Knut and Alice Wallenberg Foundation Wallenberg Academy Fellows project AtmoRemove (no. 2015.0162), the Portuguese Foundation for Science and Technology (no. CERN/FIS-COM/0014/2017) and the Technology Transfer Project N059 of the Karlsruhe Institute of Technology (KIT). The FIGAERO-CIMS was supported by a Major Research Instrumentation (MRI) grant for the US NSF AGS-1531284, as well as the Wallace Research Foundation. The computations by R.Bardakov were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Center (NSC).
N1  - Correspondence to Neil M. Donahue: nmd@andrew.cmu.edu
N1  - The EMAC (ECHAM/MESSy) model is continuously further developed and applied by a consortium of institutions. The use of MESSy
and access to the source code is licensed to all affiliates of institutions that are members of the MESSy Consortium. Institutions can
become a member of the MESSy Consortium by signing the MESSy
Memorandum of Understanding. More information can be found on
the MESSy Consortium website (https://www.messy-interface.org).
All code modifications presented in this paper will be included in the
next version of MESSy. The TOMCAT model (http://homepages.see.
leeds.ac.uk/~lecmc/tomcat.html) is a UK community model. It is available to UK (or NERC-funded) researchers who normally access the
model on common facilities or who are helped to install it on their local
machines. As it is a complex research tool, new users will need help to
use the model optimally. We do not have the resources to release and
support the model in an open way. Any potential user interested in
the model should contact Martyn Chipperfield. The model updates
described in this paper are included in the standard model library. The
cloud trajectories model is publicly available at https://doi.org/10.5281/
zenodo.5949440. Codes for conducting the analysis presented in this
paper can be obtained by contacting the corresponding author, Neil
M. Donahue (nmd@andrew.cmu.edu).
VL  - 605
SP  - 483
EP  - 489
PB  - Nature Publ. Group
CY  - London [u.a.]
ER  -