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Remote Sensing of Atmospheric Aerosol Using Spaceborne Observations

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

Deadline for manuscript submissions: closed (1 February 2023) | Viewed by 9133

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Special Issue Editors

Prof. Dr. Jan Cermak

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Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Interests: meteorology; climate; atmospheric physics; air quality
Special Issues, Collections and Topics in MDPI journals

Dr. Alexander Kokhanovsky

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Max Planck Institute for Chemistry, 55128 Mainz, Germany
Interests: cloud remote sensing; aerosol remote sensing; trace gas remote sensing; snow remote sensing; radiative transfer
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Gerrit de Leeuw

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Guest Editor

Royal Netherlands Meteorological Institute, Utrechtseweg 297, De Bilt, The Netherlands
Interests: satellite remote sensing; aerosol; clouds; climate air quality

Dr. Virginie Capelle

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Guest Editor

LMD, Ecole Polytechnique, CNRS, 91128 Palaiseau Cedex, France
Interests: radiative transfer; aerosols; surface emissivity

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 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

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

Published Papers (5 papers)

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Research

16 pages, 3751 KiB

Open AccessArticle

Study on Influencing Factors of the Information Content of Satellite Remote-Sensing Aerosol Vertical Profiles Using Oxygen A-Band

by Yuxuan Wang, Xiaobing Sun, Honglian Huang, Rufang Ti, Xiao Liu and Yizhe Fan

Remote Sens. 2023, 15(4), 948; https://doi.org/10.3390/rs15040948 - 09 Feb 2023

Cited by 2 | Viewed by 1092

Abstract

Aerosol vertical distribution is decisive and hard to be constrained. It is of great significance for the study of atmospheric climate and environment. Oxygen absorption A-bands (755–775 nm) provide a unique opportunity to acquire vertical aerosol profiles from satellites over a large spatial coverage. To investigate the ability of O₂ A-bands in retrieving aerosol vertical distribution, the dependence of retrieval on satellite observation geometry, spectral resolution, signal-to-noise ratio (SNR), size distribution, and a priori knowledge is quantified using information content theory. This work uses the radiative transfer model UNL to simulate four aerosol modes and the instrument noise model. The simulations show that a small scattering angle leads to an increase in the total amount of observed aerosol profile information, with the degrees freedom of signal (DFS) of a single band increasing from 0.4 to 0.85 at high spectral resolution (0.01 nm). The total DFS value of O₂ A-bands varies accordingly between 1.2–2.3 to 3.8–5.1 when the spectral resolution increases from 1 nm to 0.01 nm. The spectral resolution has a greater impact on DFS value than the impact from SNR (an improvement of roughly 41–53% resulted from the change in spectral resolution and the SNR led to 13–18%). The retrieval is more sensitive to aerosols with a coarse-dominated mode. The improvement in spectral resolution on information acquisition is demonstrated using the DFS and the posterior error at various previous errors and resolutions. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Aerosol Using Spaceborne Observations)

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19 pages, 5356 KiB

Open AccessArticle

FY-4A/AGRI Aerosol Optical Depth Retrieval Capability Test and Validation Based on NNAeroG

by Haonan Ding, Limin Zhao, Shanwei Liu, Xingfeng Chen, Gerrit de Leeuw, Fu Wang, Fengjie Zheng, Yuhuan Zhang, Jun Liu, Jiaguo Li, Lu She, Yidan Si and Xingfa Gu

Remote Sens. 2022, 14(21), 5591; https://doi.org/10.3390/rs14215591 - 05 Nov 2022

Cited by 2 | Viewed by 1956

Abstract

The Advanced Geostationary Radiation Imager (AGRI) is one of the main imaging sensors on the Fengyun-4A (FY-4A) satellite. Due to the combination of high spatial and temporal resolution, the AGRI is suitable for continuously monitoring atmospheric aerosol. Existing studies only perform AOD retrieval on the dark target area of FY-4A/AGRI, and the full disk AOD retrieval is still under exploration. The Neural Network AEROsol Retrieval for Geostationary Satellite (NNAeroG) based on the Fully Connected Neural Network (FCNN) was used to retrieve FY-4A/AGRI full disk aerosol optical depth (AOD). The data from 111 ground-based Aerosol Robotic Network (AERONET) and Sun–Sky Radiometer Observation Network (SONET) sites were used to train the neural network, and the data from 28 other sites were used for independent validation. FY-4A/AGRI AOD data from 2017 to 2020 were validated over the full disk and three different surface types (vegetated areas, arid areas, and marine and coastal areas). For general validation, the AOD predicted by the application of NNAeroG to FY-4A/AGRI observations is consistent with the ground-based reference AOD data. The validation of the FY-4A/AGRI AOD versus the reference data set shows that the root-mean-square error (RMSE), mean absolute error (MAE), R squared (R²), and percentage of data with errors within the expected error ± (0.05 + 15%) (EE15) are 0.237, 0.145, 0.733, and 58.7%, respectively. The AOD retrieval accuracy over vegetated areas is high but there is potential for improvement of the results over arid areas and marine and coastal areas. AOD retrieval results of FY-4A/AGRI were compared under fine and coarse modes. The retrieved AOD has low accuracy in coarse mode but is better in coarse–fine mixed mode and fine mode. The current AOD products over the ocean of NNAeroG-FY4A/AGRI are not recommended. Further development of algorithms for marine areas is expected to improve the full disk AOD retrieval accuracy. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Aerosol Using Spaceborne Observations)

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27 pages, 11106 KiB

Open AccessEditor’s ChoiceArticle

Aerosol Mineralogical Study Using Laboratory and IASI Measurements: Application to East Asian Deserts

by Perla Alalam, Lise Deschutter, Antoine Al Choueiry, Denis Petitprez and Hervé Herbin

Remote Sens. 2022, 14(14), 3422; https://doi.org/10.3390/rs14143422 - 16 Jul 2022

Cited by 5 | Viewed by 1992

Abstract

East Asia is the second-largest mineral dust source in the world, after the Sahara. When dispersed in the atmosphere, mineral dust can alter the Earth’s radiation budget by changing the atmosphere’s absorption and scattering properties. Therefore, the mineralogical composition of dust is key to understanding the impact of mineral dust on the atmosphere. This paper presents new information on mineralogical dust during East Asian dust events that were obtained from laboratory dust measurements combined with satellite remote sensing dust detections from the Infrared Atmospheric Sounding Interferometer (IASI). However, the mineral dust in this region is lifted above the continent in the lower troposphere, posing constraints due to the large variability in the Land Surface Emissivity (LSE). First, a new methodology was developed to correct the LSE from a mean monthly emissivity dataset. The results show an adjustment in the IASI spectra by acquiring aerosol information. Then, the experimental extinction coefficients of pure minerals were linearly combined to reproduce a Gobi dust spectrum, which allowed for the determination of the mineralogical mass weights. In addition, from the IASI radiances, a spectral dust optical thickness was calculated, displaying features identical to the optical thickness of the Gobi dust measured in the laboratory. The linear combination of pure minerals spectra was also applied to the IASI optical thickness, providing mineralogical mass weights. Finally, the method was applied after LSE optimization, and mineralogical evolution maps were obtained for two dust events in two different seasons and years, May 2017 and March 2021. The mean dust weights originating from the Gobi Desert, Taklamakan Desert, and Horqin Sandy Land are close to the mass weights in the literature. In addition, the spatial variability was linked to possible dust sources, and it was examined with a backward trajectory model. Moreover, a comparison between two IASI instruments on METOP-A and -B proved the method’s applicability to different METOP platforms. Due to all of the above, the applied method is a powerful tool for exploiting dust mineralogy and dust sources using both laboratory optical properties and IASI detections. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Aerosol Using Spaceborne Observations)

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12 pages, 1619 KiB

Open AccessCommunication

Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements

by Goutam Choudhury and Matthias Tesche

Remote Sens. 2022, 14(14), 3342; https://doi.org/10.3390/rs14143342 - 11 Jul 2022

Cited by 5 | Viewed by 1411

Abstract

The satellite-based cloud condensation nuclei (CCN) proxies used to quantify the aerosol-cloud interactions (ACIs) are column integrated and do not guarantee the vertical co-location of aerosols and clouds. This has encouraged the use of height-resolved measurements of spaceborne lidars for ACI studies and led to advancements in lidar-based CCN retrieval algorithms. In this study, we present a comparison between the number concentration of CCN (n_CCN) derived from ground-based in situ and spaceborne lidar cloud-aerosol lidar with orthogonal polarization (CALIOP) measurements. On analysing their monthly time series, we found that about 88% of CALIOP n_CCN estimates remained within a factor of 1.5 of the in situ measurements. Overall, the CALIOP estimates of monthly n_CCN were in good agreement with the in situ measurements with a normalized mean error of 71%, normalized mean bias of 39% and correlation coefficient of 0.68. Based on our comparison results, we point out the necessary measures that should be considered for global n_CCN retrieval. Our results show the competence of CALIOP in compiling a global height- and type-resolved n_CCN dataset for use in ACI studies. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Aerosol Using Spaceborne Observations)

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27 pages, 4934 KiB

Open AccessArticle

Using Multi-Platform Satellite Observations to Study the Atmospheric Evolution of Brown Carbon in Siberian Biomass Burning Plumes

by Igor B. Konovalov, Nikolai A. Golovushkin, Matthias Beekmann and Solène Turquety

Remote Sens. 2022, 14(11), 2625; https://doi.org/10.3390/rs14112625 - 31 May 2022

Cited by 5 | Viewed by 1661

Abstract

A bulk of evidence from in situ observations and lab experiments suggests that brown carbon (light-absorbing organic compounds in particles) can provide a significant yet highly variable contribution to the overall light absorption by aerosol particles from biomass burning (BB). Partly stemming from the complexity of the atmospheric evolution of organic aerosol (OA), the variability in brown carbon (BrC) absorption makes it difficult to partition the radiative effects of BrC and black carbon (BC) in atmospheric and climate models; as such, there are calls for satellite-based methods that could provide a statistical characterization of BrC absorption and its evolution in different regions of the world, especially in remote BB regions, such as Siberia. This study examined the feasibility of the statistical characterization of the evolution of BrC absorption and related parameters of BB aerosol in smoke plumes from intense wildfires in Siberia through the analysis of a combination of data from three satellite instruments: OMI (Ozone Monitoring Instrument), MISR (Multi-Angle Imaging SpectroRadiometer), and MODIS (Moderate Resolution Imaging Spectroradiometer). Using a Monte Carlo method, which related the satellite retrievals of the absorption and extinction aerosol optical depths to Mie theory calculations of the optical properties of BB aerosol, we found that the BrC absorption, as well as the imaginary refractive index for the OA, decreased significantly in Siberian BB smoke plumes during about 30 h of the daylight evolution, nevertheless remaining considerable until at least 70 h of the daylight evolution. Overall, the study indicated that the analysis of multi-platform satellite observations of BB plumes can provide useful insights into the atmospheric evolution of BrC absorption and the partitioning of BrC and BC contributions to the total light absorption by BB aerosol. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Aerosol Using Spaceborne Observations)

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