Atmospheric pollution in Cherepovets according to remote sensing

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Abstract

BACKGROUND: Satellite monitoring of air pollutant levels is currently widely used alongside conventional methods for assessing atmospheric pollution. Satellite technologies provide information on atmospheric pollutant levels for various geographic coordinate ranges; however, their applicability, notably for assessing air quality in residential areas, is disputed.

AIM: The work aimed to assess atmospheric pollution in Cherepovets by comparing Sentinel-5P satellite data with Earth-based monitoring data.

METHODS: The study assessed geospatial data on atmospheric air quality in Cherepovets. Sentinel-5P satellite data provided by the European Space Agency under the Copernicus program were analyzed using Google Earth Engine-based software. Satellite monitoring data were compared with those from the Severstal open service for atmospheric air quality monitoring in Cherepovets.

RESULTS: Software for analyzing satellite monitoring data on atmospheric air quality in Cherepovets was developed using Google Earth Engine and JavaScript. Digital maps of nitrogen dioxide and sulfur dioxide atmospheric pollution were created. Satellite monitoring data were compared with Severstal's Earth-based monitoring data.

CONCLUSION: Software for creating digital maps of atmospheric pollution by criteria pollutants (sulfur dioxide and nitrogen dioxide) has been developed. The differences between satellite and Earth-based monitoring data on atmospheric pollution in Cherepovets were analyzed.

About the authors

Sophia A. Tsareva

Yaroslavl State Technical University; Yaroslavl State Medical University

Author for correspondence.
Email: zarew@rambler.ru
ORCID iD: 0000-0003-2099-4885
SPIN-code: 5279-4175
Scopus Author ID: 9038734600

Cand. Sci. (Chemistry), Associate Professor

Russian Federation, Yaroslavl; Yaroslavl

Elena G. Lileeva

Yaroslavl State Medical University

Email: elileeva2006@yandex.ru
ORCID iD: 0000-0001-6048-8974
SPIN-code: 4287-6652

MD, Cand. Sci. (Medicine), Associate Professor

Russian Federation, Yaroslavl

Yuri V. Tsarev

Yaroslavl State Technical University

Email: tsarevyv@ystu.ru
ORCID iD: 0000-0002-4337-2897
SPIN-code: 7991-3530

Cand. Sci. (Engineering), Associate Professor

Russian Federation, Yaroslavl

Nataliya S. Dybulina

Yaroslavl State Technical University

Email: dybulinans@gmail.com
ORCID iD: 0009-0006-4139-639X
SPIN-code: 2758-5320
Russian Federation, Yaroslavl

Sabrina F. Velimetova

Yaroslavl State Technical University

Email: sabrinavelimetova@icloud.com
ORCID iD: 0009-0007-7891-2682
Russian Federation, Yaroslavl

References

  1. Morozova AE, Sizov OS, Elagin PO, et al. Integrated assessment of atmospheric air quality in the largest cities of Russia based on TROPOMI (Sentinel-5P) data for 2019–2020. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2022;19(4):23–39. doi: 10.21046/2070-7401-2022-19-4-23-39 EDN: AKKSYT
  2. Li B, Hu Q, Gao M, et al. Physical informed neural network improving the WRF-CHEM results of air pollution using satellite-based remote sensing data. Atmospheric Environment. 2023;311:120031. doi: 10.1016/j.atmosenv.2023.120031
  3. Ababio BA, Ashong GW, Agyekum ThP, et al. Comprehensive health risk assessment of urban ambient air pollution (PM2.5, NO2 and O3) in Ghana. Ecotoxicol Environ Saf. 2025;289:117591. doi: 10.1016/j.ecoenv.2024.117591
  4. Sakti AD, Anggraini TS, Ihsan KTN, et al. Multi-air pollution risk assessment in Southeast Asia region using integrated remote sensing and socio-economic data products. Sci Total Environ. 2023;854:158825. doi: 10.1016/j.scitotenv.2022.158825
  5. Rahimi NR, Azhdarpoor A, Fouladi-Fard R. Exposure to tropospheric ozone and NO2 in the ambient air of Tehran metropolis: Spatiotemporal distribution and inhalation health risk assessment. Physics and Chemistry of the Earth. Parts A/B/C. 2024;136:103777. doi: 10.1016/j.pce.2024.103777
  6. Dammers E, Tokaya J, Mielke C, et al. Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)? Geosci Model Dev. 2024;17(12):4983–5007. doi: 10.5194/gmd-17-4983-2024 EDN: BALSGF
  7. Cersosimo A, Serio C, Masiello G. TROPOMI NO2 tropospheric column data: regridding to 1 km grid-resolution and assessment of their consistency with in situ surface observations. Remote Sensing. 2020;12(14):2212. doi: 10.3390/rs12142212
  8. Goldberg DL, Anenberg SC, Kerr GH, et al. TROPOMI NO2 in the United States: a detailed look at the annual averages, weekly cycles, effects of temperature, and correlation with surface NO2 concentrations. Earth's Future. 2021;9(4):e2020EF001665. doi: 10.1029/2020EF001665
  9. Jeong U, Hong H. Assessment of tropospheric concentrations of NO2 from the TROPOMI/Sentinel-5 precursor for the estimation of long-term exposure to surface NO2 over South Korea. Remote Sens. 2021;13(10):1877. doi: 10.3390/rs13101877

Supplementary files

Supplementary Files
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1. JATS XML
2. Fig. 1. Digital map of nitrogen dioxide (а) and sulfur dioxide (b) levels in Cherepovets according to Sentinel-5P satellite data (as of March 30, 2025). Dots indicate Earth-based monitoring stations: 1, station No. 1 (Stroitel Community Center); 2, station No. 2 (Privokzalny Square); 3, station No. 3 (Metallurg Stadium); 4, station No. 4 (Chemical Engineering College); 5, station No. 5 (Secondary School No. 7); 6, station No. 6 (Raduzhny Waterpark).

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3. Fig. 2. Nitrogen dioxide (a) and sulfur dioxide (b) levels according to Earth-based and satellite monitoring (as of March 30, 2025).

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