Monitoring NO&lt;sub&gt;2&lt;/sub&gt; content in the atmosphere of Russia using satellite data during COVID-19 pandemic

Тронин, А. А.; Kiselev, A. V.; Vasiliev, Mikhail; Sedeeva, Margarita; Nerobelov, G. M.

doi:10.21046/2070-7401-2021-18-3-309-313

Cited by 2 publications

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“…Studies of urban areas often estimate the concentrations of individual components, such as nitrogen dioxide [ 11 , 23 ]. A similar approach is practiced in Russia; examples include remote sensing of nitrogen dioxide in the air of Moscow and St. Petersburg [ 8 , 16 ], nitrogen dioxide in the air of Moscow and Moscow oblast [ 7 ], or sulfur dioxide in the air over the Norilsk industrial zone [ 3 ]. One current trend is considered to be an assessment of the dynamics of reducing pollutant emissions in urban agglomerations associated with the COVID-19 pandemic [ 18 ].…”

Section: Resultsmentioning

confidence: 99%

Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020

et al. 2022

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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.

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