Research Article
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Year 2025, Volume: 10 Issue: 2, 262 - 271
https://doi.org/10.26833/ijeg.1587122

Abstract

References

  • Adamkiewicz, G., Liddie, J., & Gaffin, J. M. (2020). The respiratory risks of ambient/outdoor air pollution. Clinics in chest medicine, 41(4), 809-824.‏
  • Pope III, C. A., Burnett, R. T., Thurston, G. D., Thun, M. J., Calle, E. E., Krewski, D., & Godleski, J. J. (2004). Cardiovascular mortality and long-term exposure to particulate air pollution: epidemiological evidence of general pathophysiological pathways of disease. Circulation, 109(1), 71-77.‏
  • Anwer, H. A., & Hassan, A. (2024). Air Quality Dynamics in Sichuan Province: Sentinel-5P Data Insights.‏
  • Li, J., Jia, K., Wei, X., Xia, M., Chen, Z., Yao, Y., ... & Zhao, L. (2022). High-spatiotemporal resolution mapping of spatiotemporally continuous atmospheric CO2 concentrations over the global continent. International Journal of Applied Earth Observation and Geoinformation, 108, 102743.‏
  • Yang, S., Lei, L., Zeng, Z., He, Z., & Zhong, H. (2019). An assessment of anthropogenic CO2 emissions by satellite-based observations in China. Sensors, 19(5), 1118.‏
  • Liu, D., Di, B., Luo, Y., Deng, X., Zhang, H., Yang, F., ... & Zhan, Y. (2019). Estimating ground-level CO concentrations across China based on the national monitoring network and MOPITT: potentially overlooked CO hotspots in the Tibetan Plateau. Atmospheric Chemistry and Physics, 19(19), 12413-12430.‏
  • Lee, H. J., & Koutrakis, P. (2014). Daily ambient NO2 concentration predictions using satellite ozone monitoring instrument NO2 data and land use regression. Environmental science & technology, 48(4), 2305-2311.‏
  • Dang, R., Jacob, D. J., Shah, V., Eastham, S. D., Fritz, T. M., Mickley, L. J., ... & Wang, J. (2023). Background nitrogen dioxide (NO 2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires. Atmospheric Chemistry and Physics, 23(11), 6271-6284.‏
  • Clark, N. A., Demers, P. A., Karr, C. J., Koehoorn, M., Lencar, C., Tamburic, L., & Brauer, M. (2010). Effect of early life exposure to air pollution on development of childhood asthma. Environmental health perspectives, 118(2), 284-290.‏
  • Gehring, U., Cyrys, J., Sedlmeir, G., Brunekreef, B., Bellander, T., Fischer, P., ... & Heinrich, J. (2002). Traffic-related air pollution and respiratory health during the first 2 yrs of life. European respiratory journal, 19(4), 690-698.‏
  • Anwer HA, Hassan A, Anwer G. Satellite-Based Analysis of Air Pollution Trends in Khartoum before and After the Conolict. Ann Civil Environ Eng. 2025; 9(1): 001-011.‏
  • Delfino, R. J. (2002). Epidemiologic evidence for asthma and exposure to air toxics: linkages between occupational, indoor, and community air pollution research. Environmental health perspectives, 110(suppl 4), 573-589.‏
  • Qu, Z., Henze, D. K., Li, C., Theys, N., Wang, Y., Wang, J., ... & Ren, X. (2019). SO₂ Emission Estimates Using OMI SO₂ Retrievals for 2005‐2017.‏
  • Gilbert, K. M., & Shi, Y. (2024). Using GlobeLand30 data and cellular automata modeling to predict urban expansion and sprawl in Kigali City. Advanced Remote Sensing, 4(1), 46-57.‏
  • Mogaraju, J. K. (2024). Machine learning assisted prediction of land surface temperature (LST) based on major air pollutants over the Annamayya District of India. International Journal of Engineering and Geosciences, 9(2), 233-246.‏
  • Yilmaz, H. M., Yakar, M., Mutluoglu, O., Kavurmaci, M. M., & Yurt, K. (2012). Monitoring of soil erosion in Cappadocia region (Selime-Aksaray-Turkey). Environmental Earth Sciences, 66, 75-81.‏
  • Huang, R. J., Zhang, Y., Bozzetti, C., Ho, K. F., Cao, J. J., Han, Y., ... & Prévôt, A. S. (2014). High secondary aerosol contribution to particulate pollution during haze events in China. Nature, 514(7521), 218-222.‏
  • Tawfeeq, A. F., & Atasever, Ü. H. (2023). Wetland monitoring by remote sensing techniques: A case study of Işıklı Lake. Advanced Remote Sensing, 3(1), 19-26.‏
  • Burnett, R. T., Pope III, C. A., Ezzati, M., Olives, C., Lim, S. S., Mehta, S., ... & Cohen, A. (2014). An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environmental health perspectives, 122(4), 397-403.‏
  • Hoek, G., Krishnan, R. M., Beelen, R., Peters, A., Ostro, B., Brunekreef, B., & Kaufman, J. D. (2013). Long-term air pollution exposure and cardio-respiratory mortality: a review. Environmental health, 12, 1-16.‏
  • Zhang, Y., Ding, Z., Xiang, Q., Wang, W., Huang, L., & Mao, F. (2020). Short-term effects of ambient PM1 and PM2. 5 air pollution on hospital admission for respiratory diseases: Case-crossover evidence from Shenzhen, China. International journal of hygiene and environmental health, 224, 113418.‏
  • Ye, W. F., Ma, Z. Y., & Ha, X. Z. (2018). Spatial-temporal patterns of PM2. 5 concentrations for 338 Chinese cities. Science of The Total Environment, 631, 524-533.‏
  • Akar, Ö., Saralıoğlu, E., Güngör, O., & Bayata, H. F. (2024). Semantic segmentation of very-high spatial resolution satellite images: A comparative analysis of 3D-CNN and traditional machine learning algorithms for automatic vineyard detection. International Journal of Engineering and Geosciences, 9(1), 12-24.‏
  • Guo, Y., Feng, N., Christopher, S. A., Kang, P., Zhan, F. B., & Hong, S. (2014). Satellite remote sensing of fine particulate matter (PM2. 5) air quality over Beijing using MODIS. International Journal of Remote Sensing, 35(17), 6522-6544.‏
  • Alvarado, M. J., McVey, A. E., Hegarty, J. D., Cross, E. S., Hasenkopf, C. A., Lynch, R., ... & Kleiman, G. (2019). Evaluating the use of satellite observations to supplement ground-level air quality data in selected cities in low-and middle-income countries. Atmospheric Environment, 218, 117016.‏
  • Vîrghileanu, M., Săvulescu, I., Mihai, B. A., Nistor, C., & Dobre, R. (2020). Nitrogen Dioxide (NO2) Pollution monitoring with Sentinel-5P satellite imagery over Europe during the coronavirus pandemic outbreak. Remote Sensing, 12(21), 3575.‏
  • Oxoli, D., Cedeno Jimenez, J. R., & Brovelli, M. A. (2020). Assessment of SENTINEL-5P performance for ground-level air quality monitoring: preparatory experiments over the COVID-19 lockdown period. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 111-116.‏
  • Cofano, A., Cigna, F., Santamaria Amato, L., Siciliani de Cumis, M., & Tapete, D. (2021). Exploiting Sentinel-5P TROPOMI and ground sensor data for the detection of volcanic SO2 plumes and activity in 2018–2021 at Stromboli, Italy. Sensors, 21(21), 6991.‏
  • Werkmeister, A. A., Carrel, A., Porwal, N., Clemente, C., & Macdonald, M. (2023, October). Monitoring ship emissions using Sentinel-5P and AIS data. In Earth Resources and Environmental Remote Sensing/GIS Applications XIV (Vol. 12734, pp. 87-98).
  • Mathew, A., Shekar, P. R., Nair, A. T., Mallick, J., Rathod, C., Bindajam, A. A., ... & Abdo, H. G. (2024). Unveiling urban air quality dynamics during COVID-19: a Sentinel-5P TROPOMI hotspot analysis. Scientific Reports, 14(1), 21624.‏
  • Luo, Y., Zhao, T., Yang, Y., Zong, L., Kumar, K. R., Wang, H., ... & Xin, Y. (2022). Seasonal changes in the recent decline of combined high PM2. 5 and O3 pollution and associated chemical and meteorological drivers in the Beijing–Tianjin–Hebei region, China. Science of the Total Environment, 838, 156312.‏
  • Veefkind, J. P., Aben, I., McMullan, K., Förster, H., De Vries, J., Otter, G., ... & Levelt, P. F. (2012). TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications. Remote sensing of environment, 120, 70-83.‏
  • Ialongo, I., Virta, H., Eskes, H., Hovila, J., & Douros, J. (2020). Comparison of TROPOMI/Sentinel-5 Precursor NO 2 observations with ground-based measurements in Helsinki. Atmospheric measurement techniques, 13(1), 205-218.‏
  • Unel, F. B., Kusak, L., & Yakar, M. (2023). GeoValueIndex map of public property assets generating via Analytic Hierarchy Process and Geographic Information System for Mass Appraisal: GeoValueIndex. Aestimum, 82, 51-69.‏
  • Fioletov, V. E., McLinden, C. A., Krotkov, N., Li, C., Joiner, J., Theys, N., ... & Moran, M. D. (2016). A global catalogue of large SO 2 sources and emissions derived from the Ozone Monitoring Instrument. Atmospheric Chemistry and Physics, 16(18), 11497-11519.‏
  • Lorente, A., Boersma, K. F., Eskes, H. J., Veefkind, J. P., Van Geffen, J. H. G. M., De Zeeuw, M. B., ... & Krol, M. C. (2019). Quantification of nitrogen oxides emissions from build-up of pollution over Paris with TROPOMI. Scientific reports, 9(1), 20033.

A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants

Year 2025, Volume: 10 Issue: 2, 262 - 271
https://doi.org/10.26833/ijeg.1587122

Abstract

Air pollution is an escalating concern for both environmental sustainability and public health, exacerbated by urbanization and industrial growth. In Saudi Arabia, pollutants primarily from industrial activities and vehicle emissions present significant health hazards. This study utilizes data from the Sentinel-5P satellite to analyze the variations in Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Sulfur Dioxide (SO₂), and Particulate Matter (PM2.5) over a five-year period, from January 2019 to December 2023. The data was processed using Google Earth Engine (GEE) to produce monthly and seasonal averages, while ArcGIS Pro was used to map trends and spatial distribution. The results reveal distinct seasonal fluctuations in pollution levels, with CO peaking between March-May and July-September but showing an overall decline. NO₂ and SO₂ exhibit seasonal highs with slight upward trends, likely linked to industrial output and traffic emissions. PM2.5, the most harmful pollutant to human health, consistently surpasses World Health Organization (WHO) limits, especially during high-emission periods. These findings underscore the urgency of adopting targeted measures to mitigate pollution during critical times and safeguard public health. The seasonal spikes, particularly in industrial and densely populated regions, highlight the need for improved policies and technologies to effectively monitor and manage air quality

References

  • Adamkiewicz, G., Liddie, J., & Gaffin, J. M. (2020). The respiratory risks of ambient/outdoor air pollution. Clinics in chest medicine, 41(4), 809-824.‏
  • Pope III, C. A., Burnett, R. T., Thurston, G. D., Thun, M. J., Calle, E. E., Krewski, D., & Godleski, J. J. (2004). Cardiovascular mortality and long-term exposure to particulate air pollution: epidemiological evidence of general pathophysiological pathways of disease. Circulation, 109(1), 71-77.‏
  • Anwer, H. A., & Hassan, A. (2024). Air Quality Dynamics in Sichuan Province: Sentinel-5P Data Insights.‏
  • Li, J., Jia, K., Wei, X., Xia, M., Chen, Z., Yao, Y., ... & Zhao, L. (2022). High-spatiotemporal resolution mapping of spatiotemporally continuous atmospheric CO2 concentrations over the global continent. International Journal of Applied Earth Observation and Geoinformation, 108, 102743.‏
  • Yang, S., Lei, L., Zeng, Z., He, Z., & Zhong, H. (2019). An assessment of anthropogenic CO2 emissions by satellite-based observations in China. Sensors, 19(5), 1118.‏
  • Liu, D., Di, B., Luo, Y., Deng, X., Zhang, H., Yang, F., ... & Zhan, Y. (2019). Estimating ground-level CO concentrations across China based on the national monitoring network and MOPITT: potentially overlooked CO hotspots in the Tibetan Plateau. Atmospheric Chemistry and Physics, 19(19), 12413-12430.‏
  • Lee, H. J., & Koutrakis, P. (2014). Daily ambient NO2 concentration predictions using satellite ozone monitoring instrument NO2 data and land use regression. Environmental science & technology, 48(4), 2305-2311.‏
  • Dang, R., Jacob, D. J., Shah, V., Eastham, S. D., Fritz, T. M., Mickley, L. J., ... & Wang, J. (2023). Background nitrogen dioxide (NO 2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires. Atmospheric Chemistry and Physics, 23(11), 6271-6284.‏
  • Clark, N. A., Demers, P. A., Karr, C. J., Koehoorn, M., Lencar, C., Tamburic, L., & Brauer, M. (2010). Effect of early life exposure to air pollution on development of childhood asthma. Environmental health perspectives, 118(2), 284-290.‏
  • Gehring, U., Cyrys, J., Sedlmeir, G., Brunekreef, B., Bellander, T., Fischer, P., ... & Heinrich, J. (2002). Traffic-related air pollution and respiratory health during the first 2 yrs of life. European respiratory journal, 19(4), 690-698.‏
  • Anwer HA, Hassan A, Anwer G. Satellite-Based Analysis of Air Pollution Trends in Khartoum before and After the Conolict. Ann Civil Environ Eng. 2025; 9(1): 001-011.‏
  • Delfino, R. J. (2002). Epidemiologic evidence for asthma and exposure to air toxics: linkages between occupational, indoor, and community air pollution research. Environmental health perspectives, 110(suppl 4), 573-589.‏
  • Qu, Z., Henze, D. K., Li, C., Theys, N., Wang, Y., Wang, J., ... & Ren, X. (2019). SO₂ Emission Estimates Using OMI SO₂ Retrievals for 2005‐2017.‏
  • Gilbert, K. M., & Shi, Y. (2024). Using GlobeLand30 data and cellular automata modeling to predict urban expansion and sprawl in Kigali City. Advanced Remote Sensing, 4(1), 46-57.‏
  • Mogaraju, J. K. (2024). Machine learning assisted prediction of land surface temperature (LST) based on major air pollutants over the Annamayya District of India. International Journal of Engineering and Geosciences, 9(2), 233-246.‏
  • Yilmaz, H. M., Yakar, M., Mutluoglu, O., Kavurmaci, M. M., & Yurt, K. (2012). Monitoring of soil erosion in Cappadocia region (Selime-Aksaray-Turkey). Environmental Earth Sciences, 66, 75-81.‏
  • Huang, R. J., Zhang, Y., Bozzetti, C., Ho, K. F., Cao, J. J., Han, Y., ... & Prévôt, A. S. (2014). High secondary aerosol contribution to particulate pollution during haze events in China. Nature, 514(7521), 218-222.‏
  • Tawfeeq, A. F., & Atasever, Ü. H. (2023). Wetland monitoring by remote sensing techniques: A case study of Işıklı Lake. Advanced Remote Sensing, 3(1), 19-26.‏
  • Burnett, R. T., Pope III, C. A., Ezzati, M., Olives, C., Lim, S. S., Mehta, S., ... & Cohen, A. (2014). An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environmental health perspectives, 122(4), 397-403.‏
  • Hoek, G., Krishnan, R. M., Beelen, R., Peters, A., Ostro, B., Brunekreef, B., & Kaufman, J. D. (2013). Long-term air pollution exposure and cardio-respiratory mortality: a review. Environmental health, 12, 1-16.‏
  • Zhang, Y., Ding, Z., Xiang, Q., Wang, W., Huang, L., & Mao, F. (2020). Short-term effects of ambient PM1 and PM2. 5 air pollution on hospital admission for respiratory diseases: Case-crossover evidence from Shenzhen, China. International journal of hygiene and environmental health, 224, 113418.‏
  • Ye, W. F., Ma, Z. Y., & Ha, X. Z. (2018). Spatial-temporal patterns of PM2. 5 concentrations for 338 Chinese cities. Science of The Total Environment, 631, 524-533.‏
  • Akar, Ö., Saralıoğlu, E., Güngör, O., & Bayata, H. F. (2024). Semantic segmentation of very-high spatial resolution satellite images: A comparative analysis of 3D-CNN and traditional machine learning algorithms for automatic vineyard detection. International Journal of Engineering and Geosciences, 9(1), 12-24.‏
  • Guo, Y., Feng, N., Christopher, S. A., Kang, P., Zhan, F. B., & Hong, S. (2014). Satellite remote sensing of fine particulate matter (PM2. 5) air quality over Beijing using MODIS. International Journal of Remote Sensing, 35(17), 6522-6544.‏
  • Alvarado, M. J., McVey, A. E., Hegarty, J. D., Cross, E. S., Hasenkopf, C. A., Lynch, R., ... & Kleiman, G. (2019). Evaluating the use of satellite observations to supplement ground-level air quality data in selected cities in low-and middle-income countries. Atmospheric Environment, 218, 117016.‏
  • Vîrghileanu, M., Săvulescu, I., Mihai, B. A., Nistor, C., & Dobre, R. (2020). Nitrogen Dioxide (NO2) Pollution monitoring with Sentinel-5P satellite imagery over Europe during the coronavirus pandemic outbreak. Remote Sensing, 12(21), 3575.‏
  • Oxoli, D., Cedeno Jimenez, J. R., & Brovelli, M. A. (2020). Assessment of SENTINEL-5P performance for ground-level air quality monitoring: preparatory experiments over the COVID-19 lockdown period. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 111-116.‏
  • Cofano, A., Cigna, F., Santamaria Amato, L., Siciliani de Cumis, M., & Tapete, D. (2021). Exploiting Sentinel-5P TROPOMI and ground sensor data for the detection of volcanic SO2 plumes and activity in 2018–2021 at Stromboli, Italy. Sensors, 21(21), 6991.‏
  • Werkmeister, A. A., Carrel, A., Porwal, N., Clemente, C., & Macdonald, M. (2023, October). Monitoring ship emissions using Sentinel-5P and AIS data. In Earth Resources and Environmental Remote Sensing/GIS Applications XIV (Vol. 12734, pp. 87-98).
  • Mathew, A., Shekar, P. R., Nair, A. T., Mallick, J., Rathod, C., Bindajam, A. A., ... & Abdo, H. G. (2024). Unveiling urban air quality dynamics during COVID-19: a Sentinel-5P TROPOMI hotspot analysis. Scientific Reports, 14(1), 21624.‏
  • Luo, Y., Zhao, T., Yang, Y., Zong, L., Kumar, K. R., Wang, H., ... & Xin, Y. (2022). Seasonal changes in the recent decline of combined high PM2. 5 and O3 pollution and associated chemical and meteorological drivers in the Beijing–Tianjin–Hebei region, China. Science of the Total Environment, 838, 156312.‏
  • Veefkind, J. P., Aben, I., McMullan, K., Förster, H., De Vries, J., Otter, G., ... & Levelt, P. F. (2012). TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications. Remote sensing of environment, 120, 70-83.‏
  • Ialongo, I., Virta, H., Eskes, H., Hovila, J., & Douros, J. (2020). Comparison of TROPOMI/Sentinel-5 Precursor NO 2 observations with ground-based measurements in Helsinki. Atmospheric measurement techniques, 13(1), 205-218.‏
  • Unel, F. B., Kusak, L., & Yakar, M. (2023). GeoValueIndex map of public property assets generating via Analytic Hierarchy Process and Geographic Information System for Mass Appraisal: GeoValueIndex. Aestimum, 82, 51-69.‏
  • Fioletov, V. E., McLinden, C. A., Krotkov, N., Li, C., Joiner, J., Theys, N., ... & Moran, M. D. (2016). A global catalogue of large SO 2 sources and emissions derived from the Ozone Monitoring Instrument. Atmospheric Chemistry and Physics, 16(18), 11497-11519.‏
  • Lorente, A., Boersma, K. F., Eskes, H. J., Veefkind, J. P., Van Geffen, J. H. G. M., De Zeeuw, M. B., ... & Krol, M. C. (2019). Quantification of nitrogen oxides emissions from build-up of pollution over Paris with TROPOMI. Scientific reports, 9(1), 20033.
There are 36 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Article
Authors

Hossamaldeen Mohamed 0009-0008-4128-9329

Abubakr Hassan 0000-0003-1998-4559

Abdelrahim Elhag 0009-0007-8585-3780

Early Pub Date January 25, 2025
Publication Date
Submission Date November 18, 2024
Acceptance Date January 17, 2025
Published in Issue Year 2025 Volume: 10 Issue: 2

Cite

APA Mohamed, H., Hassan, A., & Elhag, A. (2025). A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants. International Journal of Engineering and Geosciences, 10(2), 262-271. https://doi.org/10.26833/ijeg.1587122
AMA Mohamed H, Hassan A, Elhag A. A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants. IJEG. January 2025;10(2):262-271. doi:10.26833/ijeg.1587122
Chicago Mohamed, Hossamaldeen, Abubakr Hassan, and Abdelrahim Elhag. “A Five-Year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-Term Trends of Atmospheric Pollutants”. International Journal of Engineering and Geosciences 10, no. 2 (January 2025): 262-71. https://doi.org/10.26833/ijeg.1587122.
EndNote Mohamed H, Hassan A, Elhag A (January 1, 2025) A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants. International Journal of Engineering and Geosciences 10 2 262–271.
IEEE H. Mohamed, A. Hassan, and A. Elhag, “A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants”, IJEG, vol. 10, no. 2, pp. 262–271, 2025, doi: 10.26833/ijeg.1587122.
ISNAD Mohamed, Hossamaldeen et al. “A Five-Year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-Term Trends of Atmospheric Pollutants”. International Journal of Engineering and Geosciences 10/2 (January 2025), 262-271. https://doi.org/10.26833/ijeg.1587122.
JAMA Mohamed H, Hassan A, Elhag A. A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants. IJEG. 2025;10:262–271.
MLA Mohamed, Hossamaldeen et al. “A Five-Year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-Term Trends of Atmospheric Pollutants”. International Journal of Engineering and Geosciences, vol. 10, no. 2, 2025, pp. 262-71, doi:10.26833/ijeg.1587122.
Vancouver Mohamed H, Hassan A, Elhag A. A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants. IJEG. 2025;10(2):262-71.