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Remote Sensing and Climate Pollutants

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: 10 February 2026 | Viewed by 590

Special Issue Editors


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Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: aerosol remote sensing; atmospheric component; climate change
Special Issues, Collections and Topics in MDPI journals
National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
Interests: microwave remote sensing calibration and quantitative inversion; hyperspectral atmospheric remote sensing; radiative transfer modeling

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Guest Editor
Faculty of Environmental and Life Sciences, University of Southampton, Southampton SO17 1BJ, UK
Interests: climate change; gross primary productivity; photosynthesis; earth observations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate pollutants are the atmospheric components that crucially impact the Earth's climate by altering the balance of energy in the atmosphere. These pollutants come from natural and human sources and can contribute to either the warming or cooling of the planet. Remote sensing can provide wide-coverage observations in adequate spatial and temporal resolution. Such characteristics mean it can be utilized for the accurate acquisition of climate pollutant concentration and analysis of the climate, environment, and health effect.

The types of climate pollutants are varied. Categorized based on their physical state, they can be classified as gaseous climate pollutants and aerosols. Categorized based on their atmospheric lifetime, they can be classified as Short-Lived Climate Pollutants (SLCPs) and Long-Lived Climate Pollutants (LLCPs). The goal of this Special Issue is to discuss the accurate acquisition of different climate pollutants using remote sensing measurements and to discuss the climate, environment, and health effect of different types of climate pollutants, revealing their underlying mechanisms.

Therefore, we cordially invite our colleagues in the scientific community to submit their recent findings on “Remote Sensing and Climate Pollutants” to this Special Issue of Remote Sensing. Potential topics include, but are not limited to, the following:

  • Remote sensing retrieval of climate pollutants;
  • Remote sensing study of Greenhouse Gases (GHGs);
  • Remote sensing study of scattering and absorbing aerosols;
  • Remote sensing study of Short-Lived Climate Pollutants (SLCPs);
  • Remote sensing study of Long-Lived Climate Pollutants (LLCPs).

Dr. Shuaiyi Shi
Dr. Jian Xu
Dr. Songyan Zhu
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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • remote sensing
  • climate pollutants
  • greenhouse gases (GHGs)
  • short-lived climate pollutants (SLCPs)
  • long-lived climate pollutants (LLCPs)
  • scattering and absorbing aerosols

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Published Papers (1 paper)

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Research

22 pages, 2479 KiB  
Article
Principles of Correction for Long-Term Orbital Observations of Atmospheric Composition, Applied to AIRS v.6 CH4 and CO Data
by Vadim Rakitin, Eugenia Fedorova, Andrey Skorokhod, Natalia Kirillova, Natalia Pankratova and Nikolai Elansky
Remote Sens. 2025, 17(13), 2323; https://doi.org/10.3390/rs17132323 - 7 Jul 2025
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Abstract
This study considers methods for assessing the quality of orbital observations, quantifying drift over time, and the application of correction methods to long-term series. AIRS v6 (IR-only) satellite methane (CH4) and carbon monoxide (CO) total column (TC) measurements were compared with [...] Read more.
This study considers methods for assessing the quality of orbital observations, quantifying drift over time, and the application of correction methods to long-term series. AIRS v6 (IR-only) satellite methane (CH4) and carbon monoxide (CO) total column (TC) measurements were compared with NDACC ground station data from 2003 to 2022. For CH4, negative trends were observed in the difference between satellite and ground measurements (AIRS-GR) at all 18 stations (mean drift: 1.69 × 1014 ± 0.31 × 1014 molecules/cm2 per day), suggesting a shift in the orbital spectrometer parameters is probable. The application of a dynamic correction based on this drift coefficient significantly improved the correlation with satellite data for both daily means and trends at all stations. In contrast, AIRS v6 CO measurements showed a strong initial correlation (R = 0.93 for the entire dataset, and R ~ 0.8–0.95 for separate stations) without systematic drift, i.e., the trends of AIRS-GR at individual sites were oppositely directed and statistically insignificant. Therefore, the AIRS v6 CO TC satellite product does not require additional correction within this method. The developed methodology for satellite data verification and correction is supposed to be universal and applicable to other long-term orbital observations. Full article
(This article belongs to the Special Issue Remote Sensing and Climate Pollutants)
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