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Title: Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory: PREDICTING DUST MINERAL COMPOSITION

Abstract

Regional variations of dust mineral composition are fundamental to climate impacts but generally neglected in climate models. A challenge for models is that atlases of soil composition are derived from measurements following wet sieving, which destroys the aggregates potentially emitted from the soil. Aggregates are crucial to simulating the observed size distribution of emitted soil particles. We use an extension of brittle fragmentation theory in a global dust model to account for these aggregates. Our method reproduces the size-resolved dust concentration along with the approximately size-invariant fractional abundance of elements like Fe and Al in the decade-long aerosol record from the Izaña Observatory, off the coast of West Africa. By distinguishing between Fe in structural and free forms, we can attribute improved model behavior to aggregation of Fe and Al-rich clay particles. We also demonstrate the importance of size-resolved measurements along with elemental composition analysis to constrain models.

Authors:
 [1];  [1];  [1];  [2];  [3]
  1. Columbia Univ., New York, NY (United States); NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)
  2. Consejo Superior de Investigaciones Cientificas (CSIC), Tenerife (Spain). Izaña Atmospheric Research Centre
  3. Univ. of Miami, FL (United States)
Publication Date:
Research Org.:
Columbia Univ., New York, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1532979
Alternate Identifier(s):
OSTI ID: 1399818
Grant/Contract Number:  
SC0006713
Resource Type:
Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Volume: 43; Journal Issue: 19; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; Geology

Citation Formats

Pérez García-Pando, Carlos, Miller, Ron L., Perlwitz, Jan P., Rodríguez, Sergio, and Prospero, Joseph M. Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory: PREDICTING DUST MINERAL COMPOSITION. United States: N. p., 2016. Web. doi:10.1002/2016gl069873.
Pérez García-Pando, Carlos, Miller, Ron L., Perlwitz, Jan P., Rodríguez, Sergio, & Prospero, Joseph M. Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory: PREDICTING DUST MINERAL COMPOSITION. United States. doi:10.1002/2016gl069873.
Pérez García-Pando, Carlos, Miller, Ron L., Perlwitz, Jan P., Rodríguez, Sergio, and Prospero, Joseph M. Wed . "Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory: PREDICTING DUST MINERAL COMPOSITION". United States. doi:10.1002/2016gl069873. https://www.osti.gov/servlets/purl/1532979.
@article{osti_1532979,
title = {Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory: PREDICTING DUST MINERAL COMPOSITION},
author = {Pérez García-Pando, Carlos and Miller, Ron L. and Perlwitz, Jan P. and Rodríguez, Sergio and Prospero, Joseph M.},
abstractNote = {Regional variations of dust mineral composition are fundamental to climate impacts but generally neglected in climate models. A challenge for models is that atlases of soil composition are derived from measurements following wet sieving, which destroys the aggregates potentially emitted from the soil. Aggregates are crucial to simulating the observed size distribution of emitted soil particles. We use an extension of brittle fragmentation theory in a global dust model to account for these aggregates. Our method reproduces the size-resolved dust concentration along with the approximately size-invariant fractional abundance of elements like Fe and Al in the decade-long aerosol record from the Izaña Observatory, off the coast of West Africa. By distinguishing between Fe in structural and free forms, we can attribute improved model behavior to aggregation of Fe and Al-rich clay particles. We also demonstrate the importance of size-resolved measurements along with elemental composition analysis to constrain models.},
doi = {10.1002/2016gl069873},
journal = {Geophysical Research Letters},
number = 19,
volume = 43,
place = {United States},
year = {2016},
month = {8}
}

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Cited by: 5 works
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