Monitoring of the Nitrogen Dioxide Concentration in the Period of Covid-19 Using Sentinel-5 Satellite Data (Case Study: Shiraz Metropolis)

Abdolazimi, Hadi; Farhadi, Hadi; Roosta, Hossein; Mokhtari, Nasrin

doi:10.22111/jneh.2023.45267.1949

Monitoring of the Nitrogen Dioxide Concentration in the Period of Covid-19 Using Sentinel-5 Satellite Data (Case Study: Shiraz Metropolis)

Document Type : Research Article

Authors

¹ Assistant Professor, Department of Remote Sensing and GIS, Shiraz Branch, Islamic Azad University, Shiraz, Iran.

² Ph.D. Student in remote sensing, Faculty of Geodesy and Geomatics Engineering, K.N Toosi University of Technology, Tehran, Iran

³ Master Student in remote sensing and GIS, Shiraz Branch, Islamic Azad University, Shiraz, Iran

⁴ Ph.D. Student in urbanism, Najafabad Branch, Islamic Azad University, Najafabad, Iran

10.22111/jneh.2023.45267.1949

Abstract

Nitrogen dioxide is considered one of the important indicators for evaluating the air quality of cities, therefore, identifying the areas contaminated with this pollutant is very important. One of the sciences and technologies that can help urban environmental experts to identify these areas in the shortest time and at a lower cost is satellite remote sensing. Currently, satellite remote sensing is a useful technology for measuring atmospheric pollutants at the global, regional, and urban levels. Therefore, the present research has identified and investigated the temporal-spatial distribution of nitrogen dioxide gas during the spread of Covid-19 using Sentinel-5P satellite data in the Shiraz metropolis for 24 months (2019 and 2020). Based on the results of this research, the highest monthly average values of nitrogen dioxide gas in 2019 and 2020 are related to the autumn season. In addition, district 2 of Shiraz was identified as the most polluted area in the two years studied. In addition, after analyzing the parameters of wind, precipitation, and temperature, it was found that the wind factor with a correlation coefficient of -0.638 at a significance level of 1% compared to other climate factors had the greatest impact on the change in nitrogen dioxide gas values. The Covid-19 crisis also played a role in changing the amount of nitrogen dioxide gas in 2020 compared to 2019 every month with its impact on the reduction of traffic and urban traffic. The pattern of changes in the average nitrogen dioxide gas related to satellite data in the studied years had a decreasing trend, which was consistent with the pattern of changes in the values obtained from the pollution monitoring station. The results of this research can be useful in urban livability and crisis management.

Keywords

Main Subjects

Environmental Management

References

References (in Persian)

Farhadi, H., Managhebi, T., & Ebadi, H. (2022). Buildings extraction in urban areas based on the radar and optical time series data using Google Earth Engine. Scientific-Research Quarterly of Geographical Data (SEPEHR), 30(120), 43-63. 10.22131/sepehr.2022.251053. [In Persian]

Hosseini, S.S., Mehrdanesh, G., & Farshad, L. (2020). The effect of COVID-19 virus on urban climate and citizens' health in urban Planning. Geography and Human Relationships, 3(2), 91-119. https://dorl.net/dor/20.1001.1.26453851.1399.3.2.9.6. [In Persian]

Irandoost, K., Isaloo, A. A., & Shahmoradi, B. (2016). Viability index in urban environments (case study: the central part of the holy city of Qom). Journal of Urban Economics and Management, 4(13), 101-118. 20.1001.1.23452870.1394.4.13.7.4. [In Persian]

Jafari, S., Hamzeh, S., Abdolazimi, H., & Attarchi, S. (2021). Two decades of monitoring Maharloo Wetland using satellite data provided by Google Earth Engine. Scientific-Research Quarterly of Geographical Data (SEPEHR), 30(118), 153-168. 10.22131/sepehr.2021.246147. [In Persian]

Kefayate Motlagh, O. R. (2020). Analysis of Inversion Indicators of Boundary Layer in Shiraz. Climate Change and Climate Disasters, 1(2), 40-54. [In Persian]

Leili, M., Bahrami Asl, F., Hesam, M., Molamahmoudi, M., & Salahshour Arian, S. (2017). Estimation of Diseases and Mortality Attributed to Atmospheric NO2 and SO2 Using AirQ Model in Hamadan City, Iran. Avicenna Journal of Clinical Medicine, 23(4), 314-322. http://dx.doi.org/10.21859/hums-230412 . [In Persian]

Najafpoor, A., Joneidi Jafari, A., & Dousti, S. (2015). Trend analysis of Air Quality Index criteria pollutants (CO, NO2, SO2, PM10, and O3) concentration changes in Tehran metropolis and its relationship with meteorological data, 2001-2009. J Health Field, 3(2), 17-26. [In Persian]

Ranjbar, M., & Bahak, B. (2019). Time and Space Changes of Air Pollutants Using GIS (Case Study: North Semnan Tehran. Geography, 17(60), 72-85. [In Persian]

Shahmohammadi, A., Bayat, A., & Mashhadizadeh Maleki, S. (2020). Study of air pollution in Tabriz City by the use of Nitrogen Dioxide OMI sensor. Geography and Planning, 24(71), 201-219. 10.22034/GP.2020.10537. [In Persian]

Shogrkhodaei, Z., Fathnia, A., & Razavi Termeh, V. (2022). Relationship between Covid-19 and changes in air pollutants using satellite imagery (Case study: Tehran, Isfahan, and Mashhad metropolises. Journal of Spatial Analysis Environmental Hazards, 9(1), 21-40. http://jsaeh.khu.ac.ir/article-1-3234-en.html. [In Persian]

Shami, S., Khoshlahjeh, M., Ghorbani, Z., Moghimi, A., Mohammadzadeh, A., & Sabet Ghadam, S. S. (2021). Evaluation of air pollution contributes to the COVID-19 pandemic in Iran using Sentinel 5 Satellite Data. Journal of Geomatics Science and Technology, 10(3), 135-146. http://jgst.issge.ir/article-1-962-en.html. [In Persian]

Tagvaee, M., Varesi, H.R., Bahman-Oraman, M. (2018). Survey of the distribution of medical land uses and its impact on urban traffic (case study: Kermanshah city center), Rahvar Promotional Scientific Quarterly, 9(17), 7-35. [In Persian]

Zalghi, E., Gravandi, S., Noorzadeh Hadad, M., Gudarzi, G.R., Shirbeigi, E., Alavi, S.S., Mohamadi, M.J (2013). Comparison of risk indicators of exposure to nitrogen dioxide pollutant on the health of citizens in southwest Iran. Journal of Torbat Heydarieh University of Medical Sciences, 2(3) 22-29. [In Persian]

References (in English)

Abdullah, S., Mansor, A. A., Napi, N. N. L. M., Mansor, W. N. W., Ahmed, A. N., Ismail, M., & Ramly, Z. T. A. (2020). Air quality status during 2020 Malaysia Movement Control Order (MCO) due to 2019 novel coronavirus (2019-nCoV) pandemic, Science of the Total Environment, 729, 139022, https://doi.org/10.1016/j.scitotenv.2020.139022.

Baldasano, J. M. (2020). COVID-19 lockdown effects on air quality by NO2 in the cities of Barcelona and Madrid (Spain), Science of the Total Environment, 741, 140353, https://doi.org/10.1016/j.scitotenv.2020.140353.

Bhattacharya, S., Ghosh, S., & Bhattacharyya, S. (2022). Analytical hierarchy process tool in Google Earth Engine platform: a case study of a tropical landfill site suitability. Environmental Monitoring and Assessment, 194(4), 276. https://doi.org/10.1007/s10661-022-09878-w

Broomandi, P., Karaca, F., Nikfal, A., Jahanbakhshi, A., Tamjidi, M., & Kim, J. R. (2020). Impact of COVID-19 event on the air quality in Iran. Aerosol and Air Quality Research, 20(8), 1793-1804. https://doi.org/10.4209/aaqr.2020.05.0205

Dasgupta, P., & Srikanth, K. (2020). Reduced air pollution during COVID-19: Learnings for sustainability from Indian Cities. Global Transitions, 2, 271-282. https://doi.org/10.1016/j.glt.2020.10.002

Farhadi, H., Mokhtarzade, M., Ebadi, H., & Beirami, B. A. (2022). Rapid and automatic burned area detection using sentinel-2 time-series images in google earth engine cloud platform: a case study over the Andika and Behbahan Regions, Iran. Environmental Monitoring and Assessment, 194(5), 369. https://doi.org/10.1007/s10661-022-10045-4.

Gama, C., Relvas, H., Lopes, M., & Monteiro, A. (2021). The impact of COVID-19 on air quality levels in Portugal: A way to assess traffic contribution. Environmental Research, 193, 110515. https://doi.org/10.1016/j.envres.2020.110515

Ganbat, G., Lee, H., Jo, H. W., Jadamba, B., & Karthe, D. (2022). Assessment of COVID-19 Impacts on Air Quality in Ulaanbaatar, Mongolia, Based on Terrestrial and Sentinel-5P TROPOMI Data. Aerosol and Air Quality Research, 22, 220196. https://doi.org/10.4209/aaqr.220196

Holloway, T., Miller, D., Anenberg, S., Diao, M., Duncan, B., Fiore, A. M., & Zondlo, M. A. (2021). Satellite monitoring for air quality and health. Annual Review of Biomedical Data Science, 4, 417-447. https://doi.org/10.1146/annurev-biodatasci-110920-093120.

Karami, E., Alizadeh, N., Farhadi, H., Abdolazimi, H., & Maghsoudi, Y. (2023). Monitoring of Land Surface Displacement Based on Sbas-Insar Time-Series and GIS Techniques: a Case Study Over the Shiraz Metropolis, Iran. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 10, 371-378. https://doi.org/10.5194/isprs-annals-X-4-W1-2022-371-2023, 2023.

Levelt, P. F., Stein Zweers, D. C., Aben, I., Bauwens, M., Borsdorff, T., De Smedt, I.& Verhoelst, T. (2022). Air quality impacts of COVID-19 lockdown measures detected from space using high spatial resolution observations of multiple trace gases from Sentinel-5P/TROPOMI. Atmospheric Chemistry and Physics, 22(15), 10319-10351. https://doi.org/10.5194/acp-22-10319-2022

Ogen, Y. (2020). Response to the commentary by Alexandra A. Chudnovsky on ‘Assessing nitrogen dioxide (NO2) levels as a contributing factor to coronavirus (COVID-19) fatality’. The Science of the total environment, 740, 139239. https://doi.org/10.1016%2Fj.scitotenv.2020.139239

Pérez-Cutillas, P., Pérez-Navarro, A., Conesa-García, C., Zema, D. A., & Amado-Álvarez, J. P. (2023). What is going on within the google earth engine? A systematic review and meta-analysis. Remote Sensing Applications: Society and Environment, 29, 100907. https://doi.org/10.1016/j.rsase.2022.100907

Saxena, A., & Raj, S. (2021). Impact of lockdown during COVID-19 pandemic on the air quality of North Indian cities. Urban Climate, 35, 100754. https://doi.org/10.1016/j.uclim.2020.100754

Sharma, S., Zhang, M., Gao, J., Zhang, H., & Kota, S. H. (2020). Effect of restricted emissions during COVID-19 on air quality in India. Science of the total environment, 728, 138878. https://doi.org/10.1016/j.scitotenv.2020.138878.

Shami, S., Ranjgar, B., Bian, J., Khoshlahjeh Azar, M., Moghimi, A., Amani, M., & Naboureh, A. (2022). Trends of CO and NO2 Pollutants in Iran during COVID-19 pandemic using Timeseries Sentinel-5 images in Google Earth Engine. Pollutants, 2(2), 156-171. https://doi.org/10.3390/pollutants2020012

Shikwambana, L., Mhangara, P., & Mbatha, N. (2020). Trend analysis and first-time observations of sulfur dioxide and nitrogen dioxide in South Africa using TROPOMI/Sentinel-5 P data. International Journal of Applied Earth Observation and Geoinformation, 91, 102130. https://doi.org/10.1016/j.jag.2020.102130.

Tobías, A., Carnerero, C., Reche, C., Massagué, J., Via, M., Minguillón, M. C., & Querol, X. (2020). Changes in air quality during the lockdown in Barcelona (Spain) one month into the SARS-CoV-2 epidemic. Science of the total environment, 726, 138540. https://doi.org/10.1016/j.scitotenv.2020.138540

Wang, Q., & Su, M. (2020). A preliminary assessment of the impact of COVID-19 on the environment–A case study of China. Science of the total environment, 728, 138915. https://doi.org/10.1016/j.scitotenv.2020.138915

World Health Organization. (2019). WHO commends Can Tho’s commitment to tackling air pollution. https://www.who.int/vietnam/news/detail/12-12-2019-who-commends-can-tho-s-commitment-to-tackle-air-pollution

Zheng, Z., Yang, Z., Wu, Z., & Marinello, F. (2019). Spatial variation of NO2 and its impact factors in China: An application of sentinel-5P products. Remote Sensing, 11(16), 1939. https://doi.org/10.3390/rs11161939.