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Remote Sensing of Atmospheric Aerosol Using Spaceborne Observations

This special issue belongs to the section “Atmospheric Remote Sensing“.

Special Issue Information

Dear Colleagues,

Atmospheric aerosol plays an important role in atmospheric physics, chemistry, and dynamics. It is one of the main factors influencing global climate change. It is known that atmospheric aerosol leads to cooling effects as compared to warming due to an increase of carbon dioxide and snow/ice darkening due to global increase of dust and black carbon load in snow and ice surfaces. It is expected that the introduction of strict measures with respect to the aerosol emissions will lead both to a decrease of mortality due to cleaner air and to a further increase of global warming.

The monitoring atmospheric aerosol and its properties using ground, airborne and spaceborne optical measurements is of importance for understanding local and global aerosol load and aerosol transport between various parts of our planet (, e.g., the transport of dust from Africa to Europe and other parts of the planet including ocean).

This Special Issue is aimed at the presentation of recent results aimed at the development of various observation systems for monitoring aerosol properties using spectral, polarimetric, dual-view and multi-angular optical instruments. The papers aimed at the description of new instrumentation for aerosol observation, and the description of modern aerosol retrieval techniques are especially welcome. Other topics to be considered are concerned with the retrieval of properties of thick aerosol plumes, simultaneous aerosol and cloud retrievals, and urban aerosol monitoring using spaceborne and ground-based optical instrumentation including lidar systems, which are of particular importance for aerosol monitoring during the night, when backscattered solar light spectral intensity and polarization cannot be used to retrieve aerosol properties.

The aim of this Special Issue is to present recent developments in ground-based and satellite remote sensing of atmospheric aerosol, such as:

  • Spaceborne aerosol retrievals over bright surfaces;
  • Multi-angular polarimetry applied for aerosol remote sensing;
  • Lidar remote sensing of atmospheric aerosol;
  • Retrievals of aerosol properties using ground-based passive optical observations;
  • Simultaneous aerosol and cloud retrieval schemes.

Dr. Alexander Kokhanovsky
Prof. Dr. Jan Cermak
Prof. Dr. Gerrit de Leeuw
Dr. Virginie Capelle
Guest EditorS

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • aerosol remote sensing
  • light scattering and absorption
  • radiative transfer
  • inverse theory
  • cloud screening
  • aerosol remote sensing over snow

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Remote Sens. - ISSN 2072-4292