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Remote Sensing
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The Future of Air Quality Monitoring by Remote Sensing
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The Future of Air Quality Monitoring by Remote Sensing

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 December 2022) | Viewed by 14824

Special Issue Editors

Dr. Yasin Elshorbany

E-Mail Website
Guest Editor
College of Arts and Sciences, University of South Florida, St. Petersburg, FL 33701, USA
Interests: atmospheric chemistry and climate; atmospheric oxidizing capacity; Arctic Climate System
Dr. Jessica Neu

E-Mail Website
Guest Editor
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Interests: remote sensing of atmospheric composition; air quality; tropospheric ozone budget

Special Issue Information

Dear Colleagues,

We would like to invite you to submit your articles regarding remote sensing applications (including data assimilation), validation, algorithms and new products to this special issue. Remote sensing techniques have the advantage of large spatial coverage, which offers a wide range of applications in air quality – from studying the earth’s atmospheric composition, large pollution episodes, to estimating emissions, predicting pollution events and planning for future missions. Satellite measurements have become essential and routinely applied in many recent studies of atmospheric composition. In the last decades, several field campaigns have been designed such that in-situ airborne and field measurements coincide with the satellite pass-over time to validate and integrate all measurements. With the recent launches of high spatial resolution, near-global coverage (e.g., TROPOMI), and high spatial and temporal resolution geostationary (GEMS, and TEMPO-to be launched in 2022) satellites, there is a revolution underway in remote sensing and its ability to address air quality issues. We invite you to submit articles on topics including, but not limited to, the following:

  • Investigation of atmospheric composition and air quality using remote sensing techniques
  • Investigation of the atmospheric oxidation capacity using OH surrogates (e.g, HCHO, isoprene)
  • Studies that involve the application of new retrieval algorithms or revised ones
  • Integrated studies of satellites, numerical modeling, and in-situ mobile or stationary measurements
  • Advances in remote sensing, retrieval algorithms, data processing, and assimilation techniques to analyze the atmospheric composition

Dr. Yasin Elshorbany
Dr. Jessica Neu
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
  • Retrieval Algorithms
  • Atmospheric Composition
  • Numerical Modelling
  • Air Quality

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

23 pages, 10133 KiB  
Article
SAMIRA-SAtellite Based Monitoring Initiative for Regional Air Quality
by Kerstin Stebel, Iwona S. Stachlewska, Anca Nemuc, Jan Horálek, Philipp Schneider, Nicolae Ajtai, Andrei Diamandi, Nina Benešová, Mihai Boldeanu, Camelia Botezan, Jana Marková, Rodica Dumitrache, Amalia Iriza-Burcă, Roman Juras, Doina Nicolae, Victor Nicolae, Petr Novotný, Horațiu Ștefănie, Lumír Vaněk, Ondrej Vlček, Olga Zawadzka-Manko and Claus Zehneradd Show full author list remove Hide full author list
Remote Sens. 2021, 13(11), 2219; https://doi.org/10.3390/rs13112219 - 5 Jun 2021
Cited by 12 | Viewed by 6024
Abstract
The satellite based monitoring initiative for regional air quality (SAMIRA) initiative was set up to demonstrate the exploitation of existing satellite data for monitoring regional and urban scale air quality. The project was carried out between May 2016 and December 2019 and focused [...] Read more.
The satellite based monitoring initiative for regional air quality (SAMIRA) initiative was set up to demonstrate the exploitation of existing satellite data for monitoring regional and urban scale air quality. The project was carried out between May 2016 and December 2019 and focused on aerosol optical depth (AOD), particulate matter (PM), nitrogen dioxide (NO2), and sulfur dioxide (SO2). SAMIRA was built around several research tasks: 1. The spinning enhanced visible and infrared imager (SEVIRI) AOD optimal estimation algorithm was improved and geographically extended from Poland to Romania, the Czech Republic and Southern Norway. A near real-time retrieval was implemented and is currently operational. Correlation coefficients of 0.61 and 0.62 were found between SEVIRI AOD and ground-based sun-photometer for Romania and Poland, respectively. 2. A retrieval for ground-level concentrations of PM2.5 was implemented using the SEVIRI AOD in combination with WRF-Chem output. For representative sites a correlation of 0.56 and 0.49 between satellite-based PM2.5 and in situ PM2.5 was found for Poland and the Czech Republic, respectively. 3. An operational algorithm for data fusion was extended to make use of various satellite-based air quality products (NO2, SO2, AOD, PM2.5 and PM10). For the Czech Republic inclusion of satellite data improved mapping of NO2 in rural areas and on an annual basis in urban background areas. It slightly improved mapping of rural and urban background SO2. The use of satellites based AOD or PM2.5 improved mapping results for PM2.5 and PM10. 4. A geostatistical downscaling algorithm for satellite-based air quality products was developed to bridge the gap towards urban-scale applications. Initial testing using synthetic data was followed by applying the algorithm to OMI NO2 data with a direct comparison against high-resolution TROPOMI NO2 as a reference, thus allowing for a quantitative assessment of the algorithm performance and demonstrating significant accuracy improvements after downscaling. We can conclude that SAMIRA demonstrated the added value of using satellite data for regional- and urban-scale air quality monitoring. Full article
(This article belongs to the Special Issue The Future of Air Quality Monitoring by Remote Sensing)
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23 pages, 4767 KiB  
Article
The Status of Air Quality in the United States During the COVID-19 Pandemic: A Remote Sensing Perspective
by Yasin F. Elshorbany, Hannah C. Kapper, Jerald R. Ziemke and Scott A. Parr
Remote Sens. 2021, 13(3), 369; https://doi.org/10.3390/rs13030369 - 21 Jan 2021
Cited by 38 | Viewed by 6308
Abstract
The recent COVID-19 pandemic has prompted global governments to take several measures to limit and contain the spread of the novel virus. In the United States (US), most states have imposed a partial to complete lockdown that has led to decreased traffic volumes [...] Read more.
The recent COVID-19 pandemic has prompted global governments to take several measures to limit and contain the spread of the novel virus. In the United States (US), most states have imposed a partial to complete lockdown that has led to decreased traffic volumes and reduced vehicle emissions. In this study, we investigate the impacts of the pandemic-related lockdown on air quality in the US using remote sensing products for nitrogen dioxide tropospheric column (NO2), carbon monoxide atmospheric column (CO), tropospheric ozone column (O3), and aerosol optical depth (AOD). We focus on states with distinctive anomalies and high traffic volume, New York (NY), Illinois (IL), Florida (FL), Texas (TX), and California (CA). We evaluate the effectiveness of reduced traffic volume to improve air quality by comparing the significant reductions during the pandemic to the interannual variability (IAV) of a respective reference period for each pollutant. We also investigate and address the potential factors that might have contributed to changes in air quality during the pandemic. As a result of the lockdown and the significant reduction in traffic volume, there have been reductions in CO and NO2. These reductions were, in many instances, compensated by local emissions and, or affected by meteorological conditions. Ozone was reduced by varying magnitude in all cases related to the decrease or increase of NO2 concentrations, depending on ozone photochemical sensitivity. Regarding the policy impacts of this large-scale experiment, our results indicate that reduction of traffic volume during the pandemic was effective in improving air quality in regions where traffic is the main pollution source, such as in New York City and FL, while was not effective in reducing pollution events where other pollution sources dominate, such as in IL, TX and CA. Therefore, policies to reduce other emissions sources (e.g., industrial emissions) should also be considered, especially in places where the reduction in traffic volume was not effective in improving air quality (AQ). Full article
(This article belongs to the Special Issue The Future of Air Quality Monitoring by Remote Sensing)
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