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Modelling of Aerosol Vertical Profiles Using Remote Sensing Techniques

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 8157

Special Issue Editor


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Guest Editor
National Institute of Research and Development for Optoelectronics, Remote Sensing Dept., Magurele, Romania
Interests: aerosol vertical profiles; remote sensing; lidar; atmospheric observation; modeling; model analysis; deep learning

Special Issue Information

Dear Colleagues,

The aerosol vertical profile is an important parameter for understanding the radiative effects of aerosols and for generating more accurate aerosol models. Despite tremendous developments and improvements in remote sensing measurement techniques for aerosols’ vertical profiles, there is still a lack of information regarding the vertical distribution of physical and chemical properties of some classes of atmospheric aerosols, especially aerosols with a complex composition such as biomass burning, dust or volcanic ash. Thus, the purpose of this Remote Sensing Special Issue is to collect scientific publications on the vertical distribution and time evolution of aerosols in the atmosphere and on their interactions with other atmospheric components (gaseous precursors, water vapor, and ozone), which could provide a comprehensive overview of aerosols and radiation, which is of great importance for studies on air quality and the climate. The Special Issue is focused on the modeling of aerosol vertical profiles using remote sensing techniques and aerosol models and aims to serve as an important contribution to the aerosol studies, as part of atmosphere research. The scientific results published in this Special Issue will also contribute conceptually to the Copernicus effort to assimilate the aerosol ground-based remote-sensing measurements in atmosphere monitoring service (CAMS).

Dr. Camelia Talianu
Guest Editor

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

  • Tropospheric profiling
  • Variability of trace gases and aerosols in the troposphere
  • Lidar remote sensing of the atmosphere
  • Aerosol transport models

Published Papers (2 papers)

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Research

17 pages, 52312 KiB  
Article
250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou
by Zhongting Wang, Ruru Deng, Pengfei Ma, Yuhuan Zhang, Yeheng Liang, Hui Chen, Shaohua Zhao and Liangfu Chen
Remote Sens. 2021, 13(5), 920; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13050920 - 01 Mar 2021
Cited by 3 | Viewed by 2046
Abstract
Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to [...] Read more.
Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ). Full article
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32 pages, 13133 KiB  
Article
Assessing Sea-State Effects on Sea-Salt Aerosol Modeling in the Lower Atmosphere Using Lidar and In-Situ Measurements
by George Varlas, Eleni Marinou, Anna Gialitaki, Nikolaos Siomos, Konstantinos Tsarpalis, Nikolaos Kalivitis, Stavros Solomos, Alexandra Tsekeri, Christos Spyrou, Maria Tsichla, Anna Kampouri, Vassilis Vervatis, Elina Giannakaki, Vassilis Amiridis, Nikolaos Mihalopoulos, Anastasios Papadopoulos and Petros Katsafados
Remote Sens. 2021, 13(4), 614; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13040614 - 09 Feb 2021
Cited by 12 | Viewed by 5226
Abstract
Atmospheric-chemical coupled models usually parameterize sea-salt aerosol (SSA) emissions using whitecap fraction estimated considering only wind speed and ignoring sea state. This approach may introduce inaccuracies in SSA simulation. This study aims to assess the impact of sea state on SSA modeling, applying [...] Read more.
Atmospheric-chemical coupled models usually parameterize sea-salt aerosol (SSA) emissions using whitecap fraction estimated considering only wind speed and ignoring sea state. This approach may introduce inaccuracies in SSA simulation. This study aims to assess the impact of sea state on SSA modeling, applying a new parameterization for whitecap fraction estimation based on wave age, calculated by the ratio between wave phase velocity and wind speed. To this end, the new parameterization was incorporated in the coupled Chemical Hydrological Atmospheric Ocean wave modeling System (CHAOS). CHAOS encompasses the wave model (WAM) two-way coupled through the OASIS3-MCT coupler with the Advanced Weather Research and Forecasting model coupled with Chemistry (WRF-ARW-Chem) and, thus, enabling the concurrent simulation of SSAs, wind speed and wave phase velocity. The simulation results were evaluated against in-situ and lidar measurements at 2 stations in Greece (Finokalia on 4 and 15 July 2014 and Antikythera-PANGEA on 15 September 2018). The results reveal significant differences between the parameterizations with the new one offering a more realistic representation of SSA levels in some layers of the lower atmosphere. This is attributed to the enhancement of the bubble-bursting mechanism representation with air-sea processes controlling whitecap fraction. Our findings also highlight the contribution of fresh wind-generated waves to SSA modeling. Full article
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