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

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 t...

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Main Authors: Matthew Fraund, Don Q. Pham, Daniel Bonanno, Tristan H. Harder, Bingbing Wang, Joel Brito, Suzane S. de Sá, Samara Carbone, Swarup China, Paulo Artaxo, Scot T. Martin, Christopher Pöhlker, Meinrat O. Andreae, Alexander Laskin, Mary K. Gilles, Ryan C. Moffet
Format: Article
Language:English
Published: MDPI AG 2017-09-01
Series:Atmosphere
Subjects:
SEM
EDX
Online Access:https://www.mdpi.com/2073-4433/8/9/173
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spelling doaj-a2491eb754df4895af76a2218470b5da2020-11-25T01:05:47ZengMDPI AGAtmosphere2073-44332017-09-018917310.3390/atmos8090173atmos8090173Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15Matthew Fraund0Don Q. Pham1Daniel Bonanno2Tristan H. Harder3Bingbing Wang4Joel Brito5Suzane S. de Sá6Samara Carbone7Swarup China8Paulo Artaxo9Scot T. Martin10Christopher Pöhlker11Meinrat O. Andreae12Alexander Laskin13Mary K. Gilles14Ryan C. Moffet15Department of Chemistry, University of the Pacific (UoP), Stockton, CA 95211, USADepartment of Chemistry, University of the Pacific (UoP), Stockton, CA 95211, USADepartment of Chemistry, University of the Pacific (UoP), Stockton, CA 95211, USAChemical Sciences Division, Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA 94720, USAEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory (PNNL), Richland, WA 99352, USAInstitute of Physics, University of Sao Paulo (USP), São Paulo 05508-020, BrazilSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USAInstitute of Physics, University of Sao Paulo (USP), São Paulo 05508-020, BrazilEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory (PNNL), Richland, WA 99352, USAInstitute of Physics, University of Sao Paulo (USP), São Paulo 05508-020, BrazilSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USABiogeochemistry Department, Max Planck Institute for Chemistry (MPIC), Mainz 55020, GermanyBiogeochemistry Department, Max Planck Institute for Chemistry (MPIC), Mainz 55020, GermanyEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory (PNNL), Richland, WA 99352, USAChemical Sciences Division, Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA 94720, USADepartment of Chemistry, University of the Pacific (UoP), Stockton, CA 95211, USATwo 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 developed environments in the Amazon Basin.https://www.mdpi.com/2073-4433/8/9/173mixing stateAmazonelemental compositionaerosolSTXMSEMEDXdiversityaging
collection DOAJ
language English
format Article
sources DOAJ
author Matthew Fraund
Don Q. Pham
Daniel Bonanno
Tristan H. Harder
Bingbing Wang
Joel Brito
Suzane S. de Sá
Samara Carbone
Swarup China
Paulo Artaxo
Scot T. Martin
Christopher Pöhlker
Meinrat O. Andreae
Alexander Laskin
Mary K. Gilles
Ryan C. Moffet
spellingShingle Matthew Fraund
Don Q. Pham
Daniel Bonanno
Tristan H. Harder
Bingbing Wang
Joel Brito
Suzane S. de Sá
Samara Carbone
Swarup China
Paulo Artaxo
Scot T. Martin
Christopher Pöhlker
Meinrat O. Andreae
Alexander Laskin
Mary K. Gilles
Ryan C. Moffet
Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15
Atmosphere
mixing state
Amazon
elemental composition
aerosol
STXM
SEM
EDX
diversity
aging
author_facet Matthew Fraund
Don Q. Pham
Daniel Bonanno
Tristan H. Harder
Bingbing Wang
Joel Brito
Suzane S. de Sá
Samara Carbone
Swarup China
Paulo Artaxo
Scot T. Martin
Christopher Pöhlker
Meinrat O. Andreae
Alexander Laskin
Mary K. Gilles
Ryan C. Moffet
author_sort Matthew Fraund
title Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15
title_short Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15
title_full Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15
title_fullStr Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15
title_full_unstemmed Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15
title_sort elemental mixing state of aerosol particles collected in central amazonia during goamazon2014/15
publisher MDPI AG
series Atmosphere
issn 2073-4433
publishDate 2017-09-01
description 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 developed environments in the Amazon Basin.
topic mixing state
Amazon
elemental composition
aerosol
STXM
SEM
EDX
diversity
aging
url https://www.mdpi.com/2073-4433/8/9/173
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