Articles | Volume 16, issue 24
https://doi.org/10.5194/acp-16-15709-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-15709-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction
Mira L. Pöhlker
CORRESPONDING AUTHOR
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Christopher Pöhlker
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Florian Ditas
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Thomas Klimach
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Isabella Hrabe de Angelis
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Alessandro Araújo
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Trav. Dr.
Enéas Pinheiro, Belém, PA, 66095-100, Brazil
Joel Brito
Institute of Physics, University of São Paulo, São Paulo,
05508-900, Brazil
now at: Laboratory for Meteorological Physics, University Blaise
Pascal, Clermont-Ferrand, France
Samara Carbone
Institute of Physics, University of São Paulo, São Paulo,
05508-900, Brazil
now at: Federal University of Uberlândia, Uberlândia-MG,
38408-100, Brazil
Yafang Cheng
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Xuguang Chi
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
now at: Institute for Climate and Global Change Research & School
of Atmospheric Sciences, Nanjing University, Nanjing, 210093, China
Reiner Ditz
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Sachin S. Gunthe
EWRE Division, Department of Civil Engineering, Indian Institute of
Technology Madras, Chennai 600036, India
Jürgen Kesselmeier
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Tobias Könemann
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Jošt V. Lavrič
Department of Biogeochemical Systems, Max Planck Institute for
Biogeochemistry, 07701 Jena, Germany
Scot T. Martin
School of Engineering and Applied Sciences, Harvard University,
Cambridge, MA 02138, USA
Eugene Mikhailov
St. Petersburg State University, 7/9 Universitetskaya nab, St.
Petersburg, 199034, Russia
Daniel Moran-Zuloaga
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Diana Rose
Institute for Atmospheric and Environmental Research, Goethe
University Frankfurt am Main, 60438 Frankfurt, Germany
Jorge Saturno
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Ryan Thalman
Biological, Environmental & Climate Sciences Department,
Brookhaven National Laboratory, Upton, NY 11973, USA
now at: Department of Chemistry, Snow College, Richfield, UT 84701,
USA
David Walter
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Jian Wang
Biological, Environmental & Climate Sciences Department,
Brookhaven National Laboratory, Upton, NY 11973, USA
Stefan Wolff
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Instituto Nacional de Pesquisas da Amazonia (INPA), Manaus,
69083-000, Brazil
Henrique M. J. Barbosa
Institute of Physics, University of São Paulo, São Paulo,
05508-900, Brazil
Paulo Artaxo
Institute of Physics, University of São Paulo, São Paulo,
05508-900, Brazil
Meinrat O. Andreae
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Scripps Institution of Oceanography, University of California San
Diego, La Jolla, CA 92037, USA
Ulrich Pöschl
Multiphase Chemistry and Biogeochemistry Departments, Max Planck
Institute for Chemistry, 55020 Mainz, Germany
Download
- Final revised paper (published on 20 Dec 2016)
- Supplement to the final revised paper
- Preprint (discussion started on 23 Jun 2016)
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
- Printer-friendly version
- Supplement
-
RC1: 'Referee report', Anonymous Referee #1, 01 Aug 2016
- AC2: 'Response to the referee #1 (M. L. Pöhlker et al., ACP-2016-519)', Mira L. Pöhlker, 10 Oct 2016
-
RC2: 'revision Long-term observations of atmospheric aerosol, cloud condensation nuclei concentration and hygroscopicity in the Amazon rain forest – Part 1: Size-resolved characterization and new model parameterizations for CCN pre-diction', Anonymous Referee #2, 02 Aug 2016
- AC1: 'Response to the referee #2 (M. L. Pöhlker et al., ACP-2016-519)', Mira L. Pöhlker, 10 Oct 2016
Peer-review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Mira L. Pöhlker on behalf of the Authors (18 Oct 2016)
Author's response
ED: Publish as is (07 Nov 2016) by Gilberto Fisch
AR by Mira L. Pöhlker on behalf of the Authors (14 Nov 2016)
Manuscript
Short summary
The paper presents a systematic characterization of cloud condensation nuclei (CCN) concentration in the central Amazonian atmosphere. Our results show that the CCN population in this globally important ecosystem follows a pollution-related seasonal cycle, in which it mainly depends on changes in total aerosol size distribution and to a minor extent in the aerosol chemical composition. Our results allow an efficient modeling and prediction of the CCN population based on a novel approach.
The paper presents a systematic characterization of cloud condensation nuclei (CCN)...
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