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Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020
This paper considers the level of atmospheric air pollution of the 20 largest cities in Russia in 2019–2020. The data used for the study is initially collected by a TROPOMI instrument (on the Sentinel-5P satellite), including measurements of carbon monoxide, formaldehyde, nitrogen dioxide, sulfur di...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Pleiades Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024599/ http://dx.doi.org/10.1134/S0010952522700071 |
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author | Morozova, A. E. Sizov, O. S. Elagin, P. O. Agzamov, N. A. Fedash, A. V. Lobzhanidze, N. E. |
author_facet | Morozova, A. E. Sizov, O. S. Elagin, P. O. Agzamov, N. A. Fedash, A. V. Lobzhanidze, N. E. |
author_sort | Morozova, A. E. |
collection | PubMed |
description | This paper considers the level of atmospheric air pollution of the 20 largest cities in Russia in 2019–2020. The data used for the study is initially collected by a TROPOMI instrument (on the Sentinel-5P satellite), including measurements of carbon monoxide, formaldehyde, nitrogen dioxide, sulfur dioxide, and aerosol (aerosol index). The measurements were obtained using the cloud-based platform, Google Earth Engine, which presents L3 level data available for direct analysis. The Tropomi Air Quality Index (TAQI) integrates available TROPOMI measurements into a single indicator. The calculation results showed that most of the cities under consideration (15 out of 20) have a low or higher than usual level of pollution. Formaldehyde (35.7%) and nitrogen dioxide (26.4%) play the main role in the composition of pollution particles. A significant share is occupied by sulfur dioxide (16.4%). The contribution of carbon monoxide and aerosol averages 10.8 and 10.6%, respectively. Air pollution in cities is caused by both natural (wildfires, dust storms) and anthropogenic (seasonal migrations of the population, restrictions due to the COVID-19 pandemic) factors. Estimating atmospheric pollution levels in urban areas using an integral index based on remote data (such as TAQI) can be considered as a valuable information addition to existing ground-based measuring systems within the multisensory paradigm. |
format | Online Article Text |
id | pubmed-10024599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Pleiades Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-100245992023-03-21 Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020 Morozova, A. E. Sizov, O. S. Elagin, P. O. Agzamov, N. A. Fedash, A. V. Lobzhanidze, N. E. Cosmic Res Article This paper considers the level of atmospheric air pollution of the 20 largest cities in Russia in 2019–2020. The data used for the study is initially collected by a TROPOMI instrument (on the Sentinel-5P satellite), including measurements of carbon monoxide, formaldehyde, nitrogen dioxide, sulfur dioxide, and aerosol (aerosol index). The measurements were obtained using the cloud-based platform, Google Earth Engine, which presents L3 level data available for direct analysis. The Tropomi Air Quality Index (TAQI) integrates available TROPOMI measurements into a single indicator. The calculation results showed that most of the cities under consideration (15 out of 20) have a low or higher than usual level of pollution. Formaldehyde (35.7%) and nitrogen dioxide (26.4%) play the main role in the composition of pollution particles. A significant share is occupied by sulfur dioxide (16.4%). The contribution of carbon monoxide and aerosol averages 10.8 and 10.6%, respectively. Air pollution in cities is caused by both natural (wildfires, dust storms) and anthropogenic (seasonal migrations of the population, restrictions due to the COVID-19 pandemic) factors. Estimating atmospheric pollution levels in urban areas using an integral index based on remote data (such as TAQI) can be considered as a valuable information addition to existing ground-based measuring systems within the multisensory paradigm. Pleiades Publishing 2023-03-18 2022 /pmc/articles/PMC10024599/ http://dx.doi.org/10.1134/S0010952522700071 Text en © Pleiades Publishing, Ltd. 2022, ISSN 0010-9525, Cosmic Research, 2022, Vol. 60, Suppl. 1, pp. S57–S68. © Pleiades Publishing, Ltd., 2022.Russian Text © The Author(s), 2022, published in Sovremennyie Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 2022, Vol. 19, No. 4, pp. 23–39. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Morozova, A. E. Sizov, O. S. Elagin, P. O. Agzamov, N. A. Fedash, A. V. Lobzhanidze, N. E. Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020 |
title | Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020 |
title_full | Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020 |
title_fullStr | Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020 |
title_full_unstemmed | Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020 |
title_short | Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020 |
title_sort | integral assessment of atmospheric air quality in the largest cities of russia based on tropomi (sentinel-5p) data for 2019–2020 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024599/ http://dx.doi.org/10.1134/S0010952522700071 |
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