24 Sep 2021

24 Sep 2021

Review status: a revised version of this preprint is currently under review for the journal ACP.

Identifying Chemical Aerosol Signatures using Optical Suborbital Observations: How much can optical properties tell us about aerosol composition?

Meloë S. F. Kacenelenbogen1, Qian Tan1,2, Sharon P. Burton3, Otto P. Hasekamp4, Karl D. Froyd5, Yohei Shinozuka1,2, Andreas J. Beyersdorf6, Luke Ziemba3, Kenneth L. Thornhill3, Jack E. Dibb7, Taylor Shingler8, Armin Sorooshian8, Reed W. Espinosa9,10, Vanderlei Martins10, Jose L. Jimenez5, Pedro Campuzano-Jost5, Joshua P. Schwarz11, Matthew S. Johnson1, Jens Redemann12, and Gregory L. Schuster3 Meloë S. F. Kacenelenbogen et al.
  • 1NASA Ames Research Center, Moffett Field, CA, 94035, USA
  • 2Bay Area Environmental Research Institute (BAERI), Moffett Field, CA, 94035, USA
  • 3NASA Langley Research Center, Hampton, VA, 23666, USA
  • 4SRON, Netherlands Institute for Space Research, Utrecht, 3584, Netherlands
  • 5Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO, 80309, USA
  • 6California State University, San Bernardino (CSUSB), San Bernardino, CA, 92407, USA
  • 7University of New Hampshire, Durham, NH, 03824, USA
  • 8University of Arizona, Tucson, AZ, 85721, USA
  • 9NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
  • 10University of Maryland Baltimore County (UMBC), Baltimore, MD 21250, USA
  • 11Chemical Sciences Division, NOAA Earth System Research Laboratory, Boulder, CO, USA
  • 12University of Oklahoma, Norman, OK 73019, USA

Abstract. Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models.

In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation.

We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements.

This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloë S. F. Kacenelenbogen et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-761', Anonymous Referee #1, 19 Nov 2021
  • RC2: 'Comment on acp-2021-761', Anonymous Referee #2, 20 Dec 2021
  • AC1: 'Comment on acp-2021-761', Meloe Kacenelenbogen, 21 Jan 2022

Meloë S. F. Kacenelenbogen et al.

Meloë S. F. Kacenelenbogen et al.


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Short summary
The impact of aerosols on Earth’s radiation budget and human health is important and strongly depends on their composition. One desire of our scientific community is to derive the composition of the aerosol from satellite sensors. However, satellites observe aerosol optical properties (and not aerosol composition) based on remote sensing instrumentation. This study asseses how much aerosol optical properties can tell us about aerosol composition.