Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15
1
Department of Chemistry, University of the Pacific (UoP), Stockton, CA 95211, USA
2
Chemical Sciences Division, Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA 94720, USA
3
Department of Chemistry, University of California, Berkeley, CA 94720, USA
4
Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory (PNNL), Richland, WA 99352, USA
5
Institute of Physics, University of Sao Paulo (USP), São Paulo 05508-020, Brazil
6
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
7
Biogeochemistry Department, Max Planck Institute for Chemistry (MPIC), Mainz 55020, Germany
8
Scripps Institution of Oceanography, University of California, La Jolla, CA 92093, USA
*
Author to whom correspondence should be addressed.
†
Current address: Physikalisches Institut, Universität Würzburg, Am Hubland, 97074 Würzburg, Germany.
‡
Current address: State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361005, China.
§
Current address: Department of Chemistry, Purdue University (PU), West Lafayette, IN 47907, USA.
‖
Current address: Laboratory for Meteorological Physics (LaMP), Université Clermont Auvergne, F-6300 Clermont-Ferrand 63000, France.
Atmosphere 2017, 8(9), 173; https://doi.org/10.3390/atmos8090173
Received: 31 July 2017 / Revised: 6 September 2017 / Accepted: 12 September 2017 / Published: 15 September 2017
(This article belongs to the Special Issue Morphology and Internal Mixing of Atmospheric Particles)
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 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. View Full-TextKeywords:
mixing state; Amazon; elemental composition; aerosol; STXM; SEM; EDX; diversity; aging
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Fraund, M.; Pham, D.Q.; Bonanno, D.; Harder, T.H.; Wang, B.; Brito, J.; De Sá, S.S.; Carbone, S.; China, S.; Artaxo, P.; Martin, S.T.; Pöhlker, C.; Andreae, M.O.; Laskin, A.; Gilles, M.K.; Moffet, R.C. Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15. Atmosphere 2017, 8, 173.
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