Monitoring Trends of CO, NO2, SO2, and O3 Pollutants Using Time-Series Sentinel-5 Images Based on Google Earth Engine Article Swipe
Mohammad Kazemi Garajeh
,
Giovanni Laneve
,
Hamid Reza Rezaei
,
Mostafa Sadeghnejad
,
Neda Mohamadzadeh
,
Behnam Salmani
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/pollutants3020019
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/pollutants3020019
Air pollution (AP) is a significant risk factor for public health, and its impact is becoming increasingly concerning in developing countries where it is causing a growing number of health issues. It is therefore essential to map and monitor AP sources in order to facilitate local action against them. This study aims at assessing the suitability of Sentinel-5 AP products based on Google Earth Engine (GEE) to monitor air pollutants, including CO, NO2, SO2, and O3 in Arak city, Iran from 2018 to 2019. Our process involved feeding satellite images to a cloud-free GEE platform that identified pollutant-affected areas monthly, seasonally, and annually. By coding in the JavaScript language in the GEE, four pollution parameters of Sentinel-5 satellite images were obtained. Following that, images with clouds were filtered by defining cloud filters, and average maps were extracted by defining average filters for both years. The employed model, which solely used Sentinel-5 AP products, was tested and assessed using ground data collected from the Environmental Organization of Central Province. Our findings revealed that annual CO, NO2, SO2, and O3 were estimated with RMSE of 0.13, 2.58, 4.62, and 2.36, respectively, for the year 2018. The annual CO, NO2, SO2, and O3 for the year 2019 were also calculated with RMSE of 0.17, 2.41, 4.31, and 4.6, respectively. The results demonstrated that seasonal AP was estimated with RMSE of 0.09, 5.39, 0.70, and 7.81 for CO, NO2, SO2, and O3, respectively, for the year 2018. Seasonal AP was also estimated with RMSE of 0.12, 4.99, 1.33, and 1.27 for CO, NO2, SO2, and O3, respectively, for the year 2019. The results of this study revealed that Sentinel-5 data combined with automated-based approaches, such as GEE, can perform better than traditional approaches (e.g., pollution measuring stations) for AP mapping and monitoring since they are capable of providing spatially distributed data that is sufficiently accurate.
Related Topics
Concepts
Gee
Environmental science
Satellite
Air pollution
Meteorology
Pollutant
Pollution
Mean squared error
Cloud computing
Air pollutants
Remote sensing
Atmospheric sciences
Geography
Generalized estimating equation
Statistics
Mathematics
Computer science
Engineering
Geology
Chemistry
Biology
Ecology
Aerospace engineering
Operating system
Organic chemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/pollutants3020019
- https://www.mdpi.com/2673-4672/3/2/19/pdf?version=1684743437
- OA Status
- gold
- Cited By
- 44
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4377286914
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4377286914Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/pollutants3020019Digital Object Identifier
- Title
-
Monitoring Trends of CO, NO2, SO2, and O3 Pollutants Using Time-Series Sentinel-5 Images Based on Google Earth EngineWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-05-22Full publication date if available
- Authors
-
Mohammad Kazemi Garajeh, Giovanni Laneve, Hamid Reza Rezaei, Mostafa Sadeghnejad, Neda Mohamadzadeh, Behnam SalmaniList of authors in order
- Landing page
-
https://doi.org/10.3390/pollutants3020019Publisher landing page
- PDF URL
-
https://www.mdpi.com/2673-4672/3/2/19/pdf?version=1684743437Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2673-4672/3/2/19/pdf?version=1684743437Direct OA link when available
- Concepts
-
Gee, Environmental science, Satellite, Air pollution, Meteorology, Pollutant, Pollution, Mean squared error, Cloud computing, Air pollutants, Remote sensing, Atmospheric sciences, Geography, Generalized estimating equation, Statistics, Mathematics, Computer science, Engineering, Geology, Chemistry, Biology, Ecology, Aerospace engineering, Operating system, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
44Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 26, 2024: 14, 2023: 4Per-year citation counts (last 5 years)
- References (count)
-
54Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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