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Title: 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

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). Our measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.The CCN measurements were continuously cycled through 10 levels of supersaturation ( S=0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. Furthermore, the particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode ( κ Ait = 0.14 ± 0.03), higher values for the accumulation mode ( κ Acc = 0.22 ± 0.05), and an overall mean value of κ mean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonalitymore » in total aerosol concentration. Here, we find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.« less
Authors:
 [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ; ORCiD logo [3] ;  [3] ; ORCiD logo [1] ;  [1] ;  [1] ;  [4] ; ORCiD logo [1] ;  [1] ; ORCiD logo [5] ;  [6] ;  [7] ;  [1] ;  [8] ; ORCiD logo [1] more »; ORCiD logo [1] ;  [9] ;  [1] ; ORCiD logo [9] ;  [10] ; ORCiD logo [3] ; ORCiD logo [3] ; ORCiD logo [10] ; ORCiD logo [1] « less
  1. Max Planck Society, Mainz (Germany). Max Planck Inst. for Chemistry
  2. Brazilian Agricultural Research Corporation (EMBRAPA), Belem, PA (Brazil)
  3. Univ. of Sao Paulo (Brazil). Inst. of Physics
  4. Indian Inst. of Technology (IIT), Madras (India)
  5. Max Planck Society, Jena (Germany). Max Planck Inst. for Biogeochemistry. Dept. of Biogeochemical Systems
  6. Harvard Univ., Cambridge, MA (United States). School of Engineering and Appled Sciences
  7. St. Petersburg State Univ. (Russia)
  8. Goethe Univ., Frankfurt (Germany). Inst. for Atmospheric and Environmental Research
  9. Brookhaven National Lab. (BNL), Upton, NY (United States). Biological Environmental and Climate Sciences Dept.
  10. Max Planck Society, Mainz (Germany). Max Planck Inst. for Chemistry; Univ. of California, San Diego, CA (United States). Scripps Institution of Oceanography
Publication Date:
Report Number(s):
BNL-113986-2017-JA
Journal ID: ISSN 1680-7324; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000
Grant/Contract Number:
SC00112704
Type:
Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 16; Journal Issue: 24; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1366352

Pöhlker, Mira L., Pöhlker, Christopher, Ditas, Florian, Klimach, Thomas, Hrabe de Angelis, Isabella, Araújo, Alessandro, Brito, Joel, Carbone, Samara, Cheng, Yafang, Chi, Xuguang, Ditz, Reiner, Gunthe, Sachin S., Kesselmeier, Jürgen, Könemann, Tobias, Lavrič, Jošt V., Martin, Scot T., Mikhailov, Eugene, Moran-Zuloaga, Daniel, Rose, Diana, Saturno, Jorge, Su, Hang, Thalman, Ryan, Walter, David, Wang, Jian, Wolff, Stefan, Barbosa, Henrique M. J., Artaxo, Paulo, Andreae, Meinrat O., and Pöschl, Ulrich. 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. United States: N. p., Web. doi:10.5194/acp-16-15709-2016.
Pöhlker, Mira L., Pöhlker, Christopher, Ditas, Florian, Klimach, Thomas, Hrabe de Angelis, Isabella, Araújo, Alessandro, Brito, Joel, Carbone, Samara, Cheng, Yafang, Chi, Xuguang, Ditz, Reiner, Gunthe, Sachin S., Kesselmeier, Jürgen, Könemann, Tobias, Lavrič, Jošt V., Martin, Scot T., Mikhailov, Eugene, Moran-Zuloaga, Daniel, Rose, Diana, Saturno, Jorge, Su, Hang, Thalman, Ryan, Walter, David, Wang, Jian, Wolff, Stefan, Barbosa, Henrique M. J., Artaxo, Paulo, Andreae, Meinrat O., & Pöschl, Ulrich. 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. United States. doi:10.5194/acp-16-15709-2016.
Pöhlker, Mira L., Pöhlker, Christopher, Ditas, Florian, Klimach, Thomas, Hrabe de Angelis, Isabella, Araújo, Alessandro, Brito, Joel, Carbone, Samara, Cheng, Yafang, Chi, Xuguang, Ditz, Reiner, Gunthe, Sachin S., Kesselmeier, Jürgen, Könemann, Tobias, Lavrič, Jošt V., Martin, Scot T., Mikhailov, Eugene, Moran-Zuloaga, Daniel, Rose, Diana, Saturno, Jorge, Su, Hang, Thalman, Ryan, Walter, David, Wang, Jian, Wolff, Stefan, Barbosa, Henrique M. J., Artaxo, Paulo, Andreae, Meinrat O., and Pöschl, Ulrich. 2016. "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". United States. doi:10.5194/acp-16-15709-2016. https://www.osti.gov/servlets/purl/1366352.
@article{osti_1366352,
title = {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},
author = {Pöhlker, Mira L. and Pöhlker, Christopher and Ditas, Florian and Klimach, Thomas and Hrabe de Angelis, Isabella and Araújo, Alessandro and Brito, Joel and Carbone, Samara and Cheng, Yafang and Chi, Xuguang and Ditz, Reiner and Gunthe, Sachin S. and Kesselmeier, Jürgen and Könemann, Tobias and Lavrič, Jošt V. and Martin, Scot T. and Mikhailov, Eugene and Moran-Zuloaga, Daniel and Rose, Diana and Saturno, Jorge and Su, Hang and Thalman, Ryan and Walter, David and Wang, Jian and Wolff, Stefan and Barbosa, Henrique M. J. and Artaxo, Paulo and Andreae, Meinrat O. and Pöschl, Ulrich},
abstractNote = {Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). Our measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.The CCN measurements were continuously cycled through 10 levels of supersaturation (S=0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. Furthermore, the particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), higher values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. Here, we find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.},
doi = {10.5194/acp-16-15709-2016},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 24,
volume = 16,
place = {United States},
year = {2016},
month = {12}
}