Comparative Analysis of NO₂, SO₂, CO, HCHO, and Aerosol Variations in Baghdad and Damascus Using Sentinel-5P and Giovanni Data via Google Earth Engine
محورهای موضوعی : فصلنامه علمی پژوهشی سنجش از دور راداری و نوری و سیستم اطلاعات جغرافیایی
Zeynab Hesabi
1
,
ali akbar jamali
2
,
Vahid Rahimi Zarchi
3
1 - Senior student of Islamic Azad University, Meybod Branch
2 - Assistant Professor, Department of GIS, Remote Sensing and Watershed Management, Meybod Unit, Islamic Azad University, Iran
3 - Department of Environment , Islamic Azad University, Maybod Branch, Iran
کلید واژه: Air Pollutants, Google Earth Engine, Sentinel-5P, Baghdad, Damascus,
چکیده مقاله :
Objective: This study aims to assess and analyze the distribution and levels of key atmospheric pollutants NO₂, SO₂, CO, HCHO, and Aerosols in Baghdad and Damascus from 2019 to 2022, exploring the impact of urbanization, industrial activities, and climatic conditions on air quality.
Methods: Remote sensing data from Sentinel-5P (TROPOMI) and Giovanni NASA through Google Earth Engine (GEE) were utilized to monitor atmospheric pollutants at a regional scale, providing high-resolution data for comprehensive analysis of pollutant concentration trends.
Results: The study reveals significantly higher levels of air pollution in Baghdad compared to Damascus, primarily due to its higher population density, intense industrial activities, and limited vegetation cover. Seasonal variations in pollutant levels were observed, with higher concentrations in colder months. Land use maps highlight urban sprawl in both cities, with Baghdad experiencing more extreme temperature variations and poorer air quality due to limited green spaces. Wind dynamics and runoff data further illustrate the role of climatic and geographical conditions in shaping pollutant distribution and water management needs.
Conclusion: The findings underscore the complex relationship between urbanization, pollution, and environmental factors in Baghdad and Damascus. While both cities face significant environmental challenges, Baghdad’s rapid urbanization and industrial activities make it more vulnerable to pollution. The study emphasizes the need for sustainable urban planning, effective pollution management strategies, and the integration of green spaces to mitigate environmental degradation and improve air quality. Remote sensing tools are essential for monitoring and managing pollution levels in both cities.
Objective: This study aims to assess and analyze the distribution and levels of key atmospheric pollutants NO₂, SO₂, CO, HCHO, and Aerosols in Baghdad and Damascus from 2019 to 2022, exploring the impact of urbanization, industrial activities, and climatic conditions on air quality.
Methods: Remote sensing data from Sentinel-5P (TROPOMI) and Giovanni NASA through Google Earth Engine (GEE) were utilized to monitor atmospheric pollutants at a regional scale, providing high-resolution data for comprehensive analysis of pollutant concentration trends.
Results: The study reveals significantly higher levels of air pollution in Baghdad compared to Damascus, primarily due to its higher population density, intense industrial activities, and limited vegetation cover. Seasonal variations in pollutant levels were observed, with higher concentrations in colder months. Land use maps highlight urban sprawl in both cities, with Baghdad experiencing more extreme temperature variations and poorer air quality due to limited green spaces. Wind dynamics and runoff data further illustrate the role of climatic and geographical conditions in shaping pollutant distribution and water management needs.
Conclusion: The findings underscore the complex relationship between urbanization, pollution, and environmental factors in Baghdad and Damascus. While both cities face significant environmental challenges, Baghdad’s rapid urbanization and industrial activities make it more vulnerable to pollution. The study emphasizes the need for sustainable urban planning, effective pollution management strategies, and the integration of green spaces to mitigate environmental degradation and improve air quality. Remote sensing tools are essential for monitoring and managing pollution levels in both cities.
Ali, S. M., & Mashee, F. K. (2014). Analyzing the terrorist operations in Baghdad using the RS and GIS Techniques. International Journal of Science and Research (IJSR), 3(11), 346-351. http://dx.doi.org/10.13140/2.1.2855.6489
Ghasempour, F., Sekertekin, A., & Kutoglu, S. H. (2021). Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing. Journal of Cleaner Production, 319, 128599. https://doi.org/10.1016/j.jclepro.2021.128599
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. https://doi.org/10.5194/amt-13-205-2020
Jamei, E., Jamei, Y., Seyedmahmoudian, M., Horan, B., Mekhilef, S., & Stojcevski, A. (2022). Investigating the impacts of COVID-19 lockdown on air quality, surface Urban Heat Island, air temperature and lighting energy consumption in City of Melbourne. Energy Strategy Reviews, 44, 100963. https://doi.org/10.1016/j.esr.2022.100963
Le, T. H., Nguyen, H. A., Barthelemy, X., Nguyen, T. T., Ha, Q. P., Jiang, N., ... & Riley, M. (2024, January). Visualization platform for multi-scale air pollution monitoring and forecast. In 2024 IEEE/SICE International Symposium on System Integration (SII) (pp. 01-06). IEEE. https://doi.org/10.1109/SII58957.2024.10417539
Li, D., Wu, S., Liang, Z., & Li, S. (2020). The impacts of urbanization and climate change on urban vegetation dynamics in China. Urban Forestry & Urban Greening, 54, 126764. https://doi.org/10.1016/j.ufug.2020.126764
Maurya, N. K., Pandey, P. C., Sarkar, S., Kumar, R., & Srivastava, P. K. (2022). Spatio-temporal monitoring of atmospheric pollutants using earth observation sentinel 5P TROPOMI data: impact of stubble burning a case study. ISPRS International Journal of Geo-Information, 11(5), 301. https://doi.org/10.3390/ijgi11050301
Meslmani, Y. (2004). Some trends related to air pollution in Damascus. Management of Environmental Quality: An International Journal, 15(4), 353-363. https://doi.org/10.1108/14777830410540108
Omokpariola, D. O., Nduka, J. N., & Omokpariola, P. L. (2024). Short-term trends of air quality and pollutant concentrations in Nigeria from 2018–2022 using tropospheric sentinel-5P and 3A/B satellite data. Discover Applied Sciences, 6(4), 182. https://doi.org/10.1007/s42452-024-05856-8
Rabee, A. M. (2015). Estimating the health risks associated with air pollution in Baghdad City, Iraq. Environmental Monitoring and Assessment, 187, 1-12. https://doi.org/10.1007/s10661-014-4203-x
Rain, D. (2009). Damascus: A Geographical Field Note. Geographical Review, 99(1), 94-104. https://doi.org/10.1111/j.1931-0846.2009.tb00420.x
Rana, F., Siddiqui, S., & ul-Haq, Z. (2023). Investigating the spatiotemporal distributions of NO2, SO2 and their association with NDVI in Lahore (Pakistan) and its adjoining region of Punjab (India). Journal of the Indian Society of Remote Sensing, 51(8), 1683-1696. https://doi.org/10.1007/s12524-023-01726-9
Sharma, M., Singh, K., Gautam, A. S., & Gautam, S. (2024). Longitudinal Study of Air Pollutants in Indian Metropolises: Seasonal Patterns and Urban Variability. Aerosol Science and Engineering, 1-16. https://doi.org/10.1007/s41810-024-00262-4
Sicard, P., Agathokleous, E., Anenberg, S. C., De Marco, A., Paoletti, E., & Calatayud, V. (2023). Trends in urban air pollution over the last two decades: A global perspective. Science of The Total Environment, 858, 160064. https://doi.org/10.1016/j.scitotenv.2022.160064
Soleimanpour, M., Alizadeh, O., & Sabetghadam, S. (2023). Analysis of diurnal to seasonal variations and trends in air pollution potential in an urban area. Scientific Reports, 13(1), 21065. https://doi.org/10.1038/s41598-023-48420-x
Xia, H., Wang, D., Abad, G. G., Yang, X., Zhu, L., Pu, D., ... & Wang, J. (2024). Multi-scale correlation reveals the evolution of socio-natural contributions to tropospheric HCHO over China from 2005 to 2022. Science of The Total Environment, 954, 176197. https://doi.org/10.1016/j.scitotenv.2024.176197
Yilmaz, O. S., Acar, U., Sanli, F. B., Gulgen, F., & Ates, A. M. (2023). Mapping burn severity and monitoring CO content in Türkiye’s 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform. Earth science informatics, 16(1), 221-240. https://doi.org/10.1007/s12145-023-00933-9
Zarin, T., & Esraz-Ul-Zannat, M. (2023). Assessing the potential impacts of LULC change on urban air quality in Dhaka city. Ecological Indicators, 154, 110746. https://doi.org/10.1016/j.ecolind.2023.110746
