skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15

Abstract

Two complementary techniques, Scanning Transmission X-ray Microscopy/Near Edge Fine Structure spectroscopy (STXM/NEXAFS) and Scanning Electron Microscopy/Energy Dispersive X-ray spectroscopy (SEM/EDX), have been quantitatively combined to characterize individual atmospheric particles. This pair of techniques was applied to particle samples at three sampling sites (ATTO, ZF2, and T3) in the Amazon basin as part of the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) field campaign during the dry season of 2014. The combined data was subjected to k-means clustering using mass fractions of the following elements: C, N, O, Na, Mg, P, S, Cl, K, Ca, Mn, Fe, Ni, and Zn. Cluster analysis identified 12 particle types, across different sampling sites and particle sizes. Samples from the remote Amazon Tall Tower Observatory (ATTO, also T0a) exhibited less cluster variety and fewer anthropogenic clusters than samples collected at the sites nearer to the Manaus metropolitan region, ZF2 (also T0t) or T3. Samples from the ZF2 site contained aged/anthropogenic clusters not readily explained by transport from ATTO or Manaus, possibly suggesting the effects of long range atmospheric transport or other local aerosol sources present during sampling. In addition, this data set allowed for recently established diversity parameters to be calculated. All samplemore » periods had high mixing state indices (χ) that were >0.8. Two individual particle diversity (D i) populations were observed, with particles <0.5 μm having a D i of ~2.4 and >0.5 μm particles having a D i of ~3.6, which likely correspond to fresh and aged aerosols respectively. The diversity parameters determined by the quantitative method presented here will serve to aid in the accurate representation of aerosol mixing state, source apportionment, and aging in both less polluted and more industrialized environments in the Amazon Basin.« less

Authors:
 [1];  [1];  [1];  [2];  [3];  [4];  [5];  [4];  [3];  [4];  [6];  [7];  [8];  [3];  [9];  [1]
  1. Univ. of the Pacific, Stockton, CA (United States). Department of Chemistry
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Chemical Sciences Division; Univ. of California, Berkeley, CA (United States). Department of Chemistry
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
  4. University of Sao Paulo (USP) (Brazil). Institute of Physics
  5. Harvard Univ., Cambridge, MA (United States). School of Engineering and Applied Sciences
  6. Harvard Univ., Cambridge, MA (United States). School of Engineering and Applied Sciences
  7. Max Planck Institute for Chemistry (MPIC), Mainz (Germany). Biogeochemistry Department
  8. Max Planck Institute for Chemistry (MPIC), Mainz (Germany). Biogeochemistry Department ; University of California, La Jolla, CA (United States). Scripps Institution of Oceanography
  9. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Chemical Sciences Division
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division; USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1406687
Alternate Identifier(s):
OSTI ID: 1468342
Report Number(s):
PNNL-SA-129528
Journal ID: ISSN 2073-4433; ATMOCZ; 48856; 49230; KP1704020
Grant/Contract Number:  
AC05-76RL01830; SC0013960; AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Atmosphere (Basel)
Additional Journal Information:
Journal Name: Atmosphere (Basel); Journal Volume: 8; Journal Issue: 9; Journal ID: ISSN 2073-4433
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; mixing state; Amazon; Elemental Composition; Aerosol; STXM; SEM; EDX; Diversity; Aging; Environmental Molecular Sciences Laboratory

Citation Formats

Fraund, Matthew, Pham, Don, Bonanno, Daniel, Harder, Tristan, Wang, Bingbing, Brito, Joel, de Sa, Suzane, Carbone, Samara, China, Swarup, Artaxo, Paulo, Martin, Scot, Pohlker, Christopher, Andreae, Meinrat, Laskin, Alexander, Gilles, Mary, and Moffet, Ryan. Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15. United States: N. p., 2017. Web. doi:10.3390/atmos8090173.
Fraund, Matthew, Pham, Don, Bonanno, Daniel, Harder, Tristan, Wang, Bingbing, Brito, Joel, de Sa, Suzane, Carbone, Samara, China, Swarup, Artaxo, Paulo, Martin, Scot, Pohlker, Christopher, Andreae, Meinrat, Laskin, Alexander, Gilles, Mary, & Moffet, Ryan. Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15. United States. doi:10.3390/atmos8090173.
Fraund, Matthew, Pham, Don, Bonanno, Daniel, Harder, Tristan, Wang, Bingbing, Brito, Joel, de Sa, Suzane, Carbone, Samara, China, Swarup, Artaxo, Paulo, Martin, Scot, Pohlker, Christopher, Andreae, Meinrat, Laskin, Alexander, Gilles, Mary, and Moffet, Ryan. Fri . "Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15". United States. doi:10.3390/atmos8090173. https://www.osti.gov/servlets/purl/1406687.
@article{osti_1406687,
title = {Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15},
author = {Fraund, Matthew and Pham, Don and Bonanno, Daniel and Harder, Tristan and Wang, Bingbing and Brito, Joel and de Sa, Suzane and Carbone, Samara and China, Swarup and Artaxo, Paulo and Martin, Scot and Pohlker, Christopher and Andreae, Meinrat and Laskin, Alexander and Gilles, Mary and Moffet, Ryan},
abstractNote = {Two complementary techniques, Scanning Transmission X-ray Microscopy/Near Edge Fine Structure spectroscopy (STXM/NEXAFS) and Scanning Electron Microscopy/Energy Dispersive X-ray spectroscopy (SEM/EDX), have been quantitatively combined to characterize individual atmospheric particles. This pair of techniques was applied to particle samples at three sampling sites (ATTO, ZF2, and T3) in the Amazon basin as part of the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) field campaign during the dry season of 2014. The combined data was subjected to k-means clustering using mass fractions of the following elements: C, N, O, Na, Mg, P, S, Cl, K, Ca, Mn, Fe, Ni, and Zn. Cluster analysis identified 12 particle types, across different sampling sites and particle sizes. Samples from the remote Amazon Tall Tower Observatory (ATTO, also T0a) exhibited less cluster variety and fewer anthropogenic clusters than samples collected at the sites nearer to the Manaus metropolitan region, ZF2 (also T0t) or T3. Samples from the ZF2 site contained aged/anthropogenic clusters not readily explained by transport from ATTO or Manaus, possibly suggesting the effects of long range atmospheric transport or other local aerosol sources present during sampling. In addition, this data set allowed for recently established diversity parameters to be calculated. All sample periods had high mixing state indices (χ) that were >0.8. Two individual particle diversity (Di) populations were observed, with particles <0.5 μm having a Di of ~2.4 and >0.5 μm particles having a Di of ~3.6, which likely correspond to fresh and aged aerosols respectively. The diversity parameters determined by the quantitative method presented here will serve to aid in the accurate representation of aerosol mixing state, source apportionment, and aging in both less polluted and more industrialized environments in the Amazon Basin.},
doi = {10.3390/atmos8090173},
journal = {Atmosphere (Basel)},
number = 9,
volume = 8,
place = {United States},
year = {Fri Sep 15 00:00:00 EDT 2017},
month = {Fri Sep 15 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Save / Share: