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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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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