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Title: Long-term observations of cloud condensation nuclei over the Amazon rain forest - Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols

For this study, size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted over a full seasonal cycle at the remote Amazon Tall Tower Observatory (ATTO, March 2014–February 2015). In a preceding companion paper, we presented annually and seasonally averaged data and parametrizations (Part 1; Pöhlker et al., 2016a). In the present study (Part 2), we analyze key features and implications of aerosol and CCN properties for the following characteristic atmospheric conditions: Empirically pristine rain forest (PR) conditions, where no influence of pollution was detectable, as observed during parts of the wet season from March to May. The PR episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode with D Ait ≈ 70nm and N Ait ≈ 160cm -3, weak accumulation mode with D acc ≈ 160nm and N acc ≈ 90cm -3), a chemical composition dominated by organic compounds, and relatively low particle hygroscopicity (κ Ait ≈ 0.12, κ acc ≈ 0.18). Long-range-transport (LRT) events, which frequently bring Saharan dust, African biomass smoke, and sea spray aerosols into the Amazon Basin, mostly during February to April. The LRT episodes are characterized by a dominant accumulation mode ( DAit ≈ 80nm, Nmore » Ait ≈ 120cm -3 vs. D acc ≈ 180nm, N acc ≈ 310cm -3), an increased abundance of dust and salt, and relatively high hygroscopicity (κ Ait ≈ 0.18, κ acc ≈ 0.35). The coarse mode is also significantly enhanced during these events. Biomass burning (BB) conditions characteristic for the Amazonian dry season from August to November. The BB episodes show a very strong accumulation mode (D Ait ≈ 70nm, N Ait ≈ 140cm -3 vs. D acc ≈ 170nm, N acc ≈ 3400cm -3), very high organic mass fractions (~90%), and correspondingly low hygroscopicity (κ Ait ≈ 0.14, κ acc ≈ 0.17). Mixed-pollution (MPOL) conditions with a superposition of African and Amazonian aerosol emissions during the dry season. During the MPOL episode presented here as a case study, we observed African aerosols with a broad monomodal distribution (D ≈ 130nm, N CN, 10 ≈ 1300cm -3), with high sulfate mass fractions (~20%) from volcanic sources and correspondingly high hygroscopicity (κ < 100 nm ≈ 0.14, κ > 10 nm ≈ 0.22), which were periodically mixed with fresh smoke from nearby fires (D ≈ 110nm, N CN, 10 ≈ 2800cm -3) with an organic-dominated composition and sharply decreased hygroscopicity (κ < 150 nm ≈ 0.10, κ > 150 nm ≈ 0.20). Insights into the aerosol mixing state are provided by particle hygroscopicity (κ) distribution plots, which indicate largely internal mixing for the PR aerosols (narrow κ distribution) and more external mixing for the BB, LRT, and MPOL aerosols (broad κ distributions). The CCN spectra (CCN concentration plotted against water vapor supersaturation) obtained for the different case studies indicate distinctly different regimes of cloud formation and microphysics depending on aerosol properties and meteorological conditions. The measurement results suggest that CCN activation and droplet formation in convective clouds are mostly aerosol-limited under PR and LRT conditions and updraft-limited under BB and MPOL conditions. Normalized CCN efficiency spectra (CCN divided by aerosol number concentration plotted against water vapor supersaturation) and corresponding parameterizations (Gaussian error function fits) provide a basis for further analysis and model studies of aerosol–cloud interactions in the Amazon.« less
Authors:
 [1] ;  [1] ; ORCiD logo [2] ;  [1] ; ORCiD logo [1] ;  [3] ; ORCiD logo [4] ;  [5] ; ORCiD logo [1] ;  [6] ;  [1] ;  [7] ;  [1] ;  [8] ; ORCiD logo [1] ; ORCiD logo [1] ;  [1] ; ORCiD logo [9] ;  [10] ; ORCiD logo [11] more »;  [1] ;  [12] ;  [13] ; ORCiD logo [1] ;  [14] ; ORCiD logo [1] ; ORCiD logo [15] ;  [1] ;  [16] ; ORCiD logo [3] ; ORCiD logo [17] ; ORCiD logo [1] ;  [1] « less
  1. Max Planck Inst. for Chemistry, Mainz (Germany). Multiphase Chemistry and Biogeochemistry Dept.
  2. Max Planck Inst. for Chemistry, Mainz (Germany). Multiphase Chemistry and Biogeochemistry Dept.; Braunschweig Univ. of Technology (Germany)
  3. Brazilian Agricultural Research Corp. (EMBRAPA), Belem (Brazil)
  4. Univ. of Sao Paulo (Brazil). Inst. of Physics; Univ. of Clermont Auvergne, Aubière (France). Physical Meterorology Lab.
  5. Univ. of Sao Paulo (Brazil). Inst. of Physics; Federal Univ. of Uberlandia (Brazil). Inst. of Agrarian Sciences
  6. Max Planck Inst. for Chemistry, Mainz (Germany). Multiphase Chemistry and Biogeochemistry Dept.; Nanjing Univ. (China). Inst. for Climate and Global Change Research and School of Atmospheric Sciences
  7. Indian Inst. of Technology (IIT), Madras (India). Environmental and Water Resources Engineering (EWRE) Division and Dept. of Civil Engineering
  8. Technical Univ. of Darmstadt (Germany). Inst. of Applied Geosciences
  9. Max Planck Inst. for Biogeochemistry, Jena (Germany). Dept. of Biogeochemical Systems
  10. Harvard Univ., Cambridge, MA (United States). John A. Paulson School of Engineering and Applied Sciences and Dept. of Earth and Planetary Sciences
  11. St. Petersburg State Univ. (Russian Federation)
  12. Federal Univ. of Sao Paulo (UNIFESP) (Brazil). Inst. of Environmental, Chemical and Pharmaceutical Sciences
  13. Goethe Univ., Frankfurt (Germany). Inst. of Atmospheric and Environmental Sciences; Hessian Agency for Nature Conservation, Environment and Geology (HLNUG), Wiesbaden (Germany)
  14. Brookhaven National Lab. (BNL), Upton, NY (United States). Biological, Environmental & Climate Sciences Dept.; Snow College, Richfield, UT (United States). Dept. of Chemistry
  15. Brookhaven National Lab. (BNL), Upton, NY (United States). Biological, Environmental & Climate Sciences Dept.
  16. Univ. of Sao Paulo (Brazil). Inst. of Physics
  17. Max Planck Inst. for Chemistry, Mainz (Germany). Multiphase Chemistry and Biogeochemistry Dept.; Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography
Publication Date:
Report Number(s):
BNL-208012-2018-JAAM
Journal ID: ISSN 1680-7324
Grant/Contract Number:
SC0012704; 01LB1001A; 01.11.01248.00; KA 2280/2; 11.37.220.2016; 603445; 13/05014-0; 13/50510-5; 18-17- 00076
Type:
Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 18; Journal Issue: 14; 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); Max Planck Society; German Federal Ministry of Education and Research (BMBF); Ministry of Science, Technology, Innovation and Communication (MCTIC) (Brazil); Amazon State Univ. (UEA), Manaus (Brazil); Amazonas State Research Support Foundation (FAPEAM) (Brazil); National Inst. of Amazonian Research (INPA). Large Scale Biosphere-Atmosphere Program in Amazonia (LBA); German Research Foundation (DFG); European Union (EU); Sao Paulo Research Foundation (FAPESP); Russian Science Federation (RSF); National Aeronautic and Space Administration (NASA)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1466979

Pöhlker, Mira L., Ditas, Florian, Saturno, Jorge, Klimach, Thomas, Hrabě de Angelis, Isabella, Araùjo, Alessandro C., Brito, Joel, Carbone, Samara, Cheng, Yafang, Chi, Xuguang, Ditz, Reiner, Gunthe, Sachin S., Holanda, Bruna A., Kandler, Konrad, Kesselmeier, Jürgen, Könemann, Tobias, Krüger, Ovid O., Lavrič, Jošt V., Martin, Scot T., Mikhailov, Eugene, Moran-Zuloaga, Daniel, Rizzo, Luciana V., Rose, Diana, Su, Hang, Thalman, Ryan, Walter, David, Wang, Jian, Wolff, Stefan, Barbosa, Henrique M. J., Artaxo, Paulo, Andreae, Meinrat O., Pöschl, Ulrich, and Pöhlker, Christopher. Long-term observations of cloud condensation nuclei over the Amazon rain forest - Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols. United States: N. p., Web. doi:10.5194/acp-18-10289-2018.
Pöhlker, Mira L., Ditas, Florian, Saturno, Jorge, Klimach, Thomas, Hrabě de Angelis, Isabella, Araùjo, Alessandro C., Brito, Joel, Carbone, Samara, Cheng, Yafang, Chi, Xuguang, Ditz, Reiner, Gunthe, Sachin S., Holanda, Bruna A., Kandler, Konrad, Kesselmeier, Jürgen, Könemann, Tobias, Krüger, Ovid O., Lavrič, Jošt V., Martin, Scot T., Mikhailov, Eugene, Moran-Zuloaga, Daniel, Rizzo, Luciana V., Rose, Diana, Su, Hang, Thalman, Ryan, Walter, David, Wang, Jian, Wolff, Stefan, Barbosa, Henrique M. J., Artaxo, Paulo, Andreae, Meinrat O., Pöschl, Ulrich, & Pöhlker, Christopher. Long-term observations of cloud condensation nuclei over the Amazon rain forest - Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols. United States. doi:10.5194/acp-18-10289-2018.
Pöhlker, Mira L., Ditas, Florian, Saturno, Jorge, Klimach, Thomas, Hrabě de Angelis, Isabella, Araùjo, Alessandro C., Brito, Joel, Carbone, Samara, Cheng, Yafang, Chi, Xuguang, Ditz, Reiner, Gunthe, Sachin S., Holanda, Bruna A., Kandler, Konrad, Kesselmeier, Jürgen, Könemann, Tobias, Krüger, Ovid O., Lavrič, Jošt V., Martin, Scot T., Mikhailov, Eugene, Moran-Zuloaga, Daniel, Rizzo, Luciana V., Rose, Diana, Su, Hang, Thalman, Ryan, Walter, David, Wang, Jian, Wolff, Stefan, Barbosa, Henrique M. J., Artaxo, Paulo, Andreae, Meinrat O., Pöschl, Ulrich, and Pöhlker, Christopher. 2018. "Long-term observations of cloud condensation nuclei over the Amazon rain forest - Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols". United States. doi:10.5194/acp-18-10289-2018. https://www.osti.gov/servlets/purl/1466979.
@article{osti_1466979,
title = {Long-term observations of cloud condensation nuclei over the Amazon rain forest - Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols},
author = {Pöhlker, Mira L. and Ditas, Florian and Saturno, Jorge and Klimach, Thomas and Hrabě de Angelis, Isabella and Araùjo, Alessandro C. and Brito, Joel and Carbone, Samara and Cheng, Yafang and Chi, Xuguang and Ditz, Reiner and Gunthe, Sachin S. and Holanda, Bruna A. and Kandler, Konrad and Kesselmeier, Jürgen and Könemann, Tobias and Krüger, Ovid O. and Lavrič, Jošt V. and Martin, Scot T. and Mikhailov, Eugene and Moran-Zuloaga, Daniel and Rizzo, Luciana V. and Rose, Diana 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 and Pöhlker, Christopher},
abstractNote = {For this study, size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted over a full seasonal cycle at the remote Amazon Tall Tower Observatory (ATTO, March 2014–February 2015). In a preceding companion paper, we presented annually and seasonally averaged data and parametrizations (Part 1; Pöhlker et al., 2016a). In the present study (Part 2), we analyze key features and implications of aerosol and CCN properties for the following characteristic atmospheric conditions: Empirically pristine rain forest (PR) conditions, where no influence of pollution was detectable, as observed during parts of the wet season from March to May. The PR episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode with DAit ≈ 70nm and NAit ≈ 160cm-3, weak accumulation mode with Dacc ≈ 160nm and Nacc ≈ 90cm-3), a chemical composition dominated by organic compounds, and relatively low particle hygroscopicity (κAit ≈ 0.12, κacc ≈ 0.18). Long-range-transport (LRT) events, which frequently bring Saharan dust, African biomass smoke, and sea spray aerosols into the Amazon Basin, mostly during February to April. The LRT episodes are characterized by a dominant accumulation mode (DAit ≈ 80nm, NAit ≈ 120cm-3 vs. Dacc ≈ 180nm, Nacc ≈ 310cm-3), an increased abundance of dust and salt, and relatively high hygroscopicity (κAit ≈ 0.18, κacc ≈ 0.35). The coarse mode is also significantly enhanced during these events. Biomass burning (BB) conditions characteristic for the Amazonian dry season from August to November. The BB episodes show a very strong accumulation mode (DAit ≈ 70nm, NAit ≈ 140cm-3 vs. Dacc ≈ 170nm, Nacc ≈ 3400cm-3), very high organic mass fractions (~90%), and correspondingly low hygroscopicity (κAit ≈ 0.14, κacc ≈ 0.17). Mixed-pollution (MPOL) conditions with a superposition of African and Amazonian aerosol emissions during the dry season. During the MPOL episode presented here as a case study, we observed African aerosols with a broad monomodal distribution (D ≈ 130nm, NCN, 10 ≈ 1300cm-3), with high sulfate mass fractions (~20%) from volcanic sources and correspondingly high hygroscopicity (κ < 100 nm ≈ 0.14, κ > 10 nm ≈ 0.22), which were periodically mixed with fresh smoke from nearby fires (D ≈ 110nm, NCN, 10 ≈ 2800cm-3) with an organic-dominated composition and sharply decreased hygroscopicity (κ < 150 nm ≈ 0.10, κ > 150 nm ≈ 0.20). Insights into the aerosol mixing state are provided by particle hygroscopicity (κ) distribution plots, which indicate largely internal mixing for the PR aerosols (narrow κ distribution) and more external mixing for the BB, LRT, and MPOL aerosols (broad κ distributions). The CCN spectra (CCN concentration plotted against water vapor supersaturation) obtained for the different case studies indicate distinctly different regimes of cloud formation and microphysics depending on aerosol properties and meteorological conditions. The measurement results suggest that CCN activation and droplet formation in convective clouds are mostly aerosol-limited under PR and LRT conditions and updraft-limited under BB and MPOL conditions. Normalized CCN efficiency spectra (CCN divided by aerosol number concentration plotted against water vapor supersaturation) and corresponding parameterizations (Gaussian error function fits) provide a basis for further analysis and model studies of aerosol–cloud interactions in the Amazon.},
doi = {10.5194/acp-18-10289-2018},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 14,
volume = 18,
place = {United States},
year = {2018},
month = {7}
}

Works referenced in this record:

The Green Ocean Amazon Experiment (GoAmazon2014/5) Observes Pollution Affecting Gases, Aerosols, Clouds, and Rainfall over the Rain Forest
journal, May 2017
  • Martin, S. T.; Artaxo, P.; Machado, L.
  • Bulletin of the American Meteorological Society, Vol. 98, Issue 5, p. 981-997
  • DOI: 10.1175/BAMS-D-15-00221.1

Amazon boundary layer aerosol concentration sustained by vertical transport during rainfall
journal, October 2016
  • Wang, Jian; Krejci, Radovan; Giangrande, Scott
  • Nature, Vol. 539, Issue 7629, p. 416-419
  • DOI: 10.1038/nature19819