Volume 11, Issue 3 (12-2024)
Journal of Spatial Analysis Environmental Hazards 2024, 11(3): 0-0 |
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omidvar K, yousefi ramandi R, toofani H. Investigation and monitoring of atmospheric pollution over Iran using Sentinel 5 satellite. Journal of Spatial Analysis Environmental Hazards 2024; 11 (3)
URL: http://jsaeh.khu.ac.ir/article-1-3432-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3432-en.html
1- Yazd University , komidvar@yazd.ac.ir
2- Yazd University
2- Yazd University
Abstract: (2574 Views)
Air pollution can have serious negative effects on human health, including cardiovascular and respiratory diseases. Monitoring and controlling air pollutants is very important to protect public health and the environment. Like many developing countries, Iran is facing air pollution, especially in its big cities and industrial cities. One of the powerful tools in air pollution monitoring is remote sensing methods. The aim of this study is to use relatively high-resolution satellite data to monitor air quality and air pollution using Sentinel-5 (Sentinel-5P) sensor images. In this study, a comprehensive monitoring based on the values of some of the most important air pollutants (including AI, O3, NO2, SO2, CH4 and CO) has been done using Sentinel-5 satellite images for Iran in 2019-2023. The results of this research showed that the emission of carbon monoxide and sulfur dioxide gases had a decreasing trend (in the months of June as an example of the examined month), but nitrogen dioxide gas, methane gas, ozone gas and aerosols had an increasing trend during the month. from June 2021 to 2023. In general, air pollution is more serious in the northern parts of the country, especially in big cities and several large urban gatherings. In this study, it was investigated how the levels of six air pollutants in Iran vary and differ from June 2019 to 2023. Another important result of this research is that the total amount of air pollution in 2020-2023 has faced an increasing trend compared to 2019. Also, the monitoring by Sentinel-5 satellite images shows that in recent years, Tehran has had the most polluted air in terms of carbon monoxide, nitrogen dioxide, sulfur dioxide and suspended particles (dust). Also, changes in the concentration of pollutants do not follow a specific pattern. It was also found that the GEE system is able to process a large amount of data in a very short time with high accuracy.
Keywords: Pollutants, pollution, methane (CH4), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2) and aerosol (AI), Sentinel-5P
Type of Study: Research |
Subject:
Special
Received: 2024/02/20 | Accepted: 2024/09/22 | Published: 2024/12/23
Received: 2024/02/20 | Accepted: 2024/09/22 | Published: 2024/12/23
References
1. 4. Adebayo-Ojo, T. C., Wichmann, J., Arowosegbe, O. O., Probst-Hensch, N., Schindler, C., & Künzli, N. (2022). Short-Term Effects of PM10, NO2, SO2 and O3 on Cardio-Respiratory Mortality in Cape Town, South Africa, 2006-2015. International journal of environmental research and public health, 19(13), 8078. https://doi.org/10.3390/ijerph19138078.
3. 5. Boersma, K. F., Eskes, H. J., & Brinksma, E. J. (2004). Error analysis for tropospheric NO2 retrieval from space. Journal of Geophysical Research: Atmospheres, 109(D4).
4. 6. Cao, Z., Luan, K., Zhou, P., Shen, W., Wang, Z., Zhu, W., Qiu, Z., & Wang, J. (2023). Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean. Toxics, 11(10), 813. https://doi.org/10.3390/toxics11100813.
5. 7. Chadwick, G. L., Joiner, A. M. N., Ramesh, S., Mitchell, D. A., & Nayak, D. D. (2023). McrD binds asymmetrically to methyl-coenzyme M reductase improving active-site accessibility during assembly. Proceedings of the National Academy of Sciences of the United States of America, 120(25), e2302815120. https://doi.org/10.1073/pnas.2302815120.
6. 8. Chakrabortty, R., Pal, S. C., Ghosh, M., Arabameri, A., Saha, A., Roy, P., Pradhan, B., Mondal, A., Ngo, P. T. T., Chowdhuri, I., Yunus, A. P., Sahana, M., Malik, S., & Das, B. (2023). Weather indicators and improving air quality in association with COVID-19 pandemic in India. Soft computing, 27(6), 3367–3388. https://doi.org/10.1007/s00500-021-06012-9 (Retraction published Soft comput. 2023 May 29;:1-2).
7. 9. Cooper, M. J., Martin, R. V., Hammer, M. S., Levelt, P. F., Veefkind, P., Lamsal, L. N., ... & McLinden, C. A. (2022). Global fine-scale changes in ambient NO2 during COVID-19 lockdowns. Nature, 601(7893), 380-387.
8. 10. Culková, E., Lukáčová-Chomisteková, Z., Bellová, R., Rievaj, M., Švancarová-Laštincová, J., & Tomčík, P. (2023). An Interference-Free Voltammetric Method for the Detection of Sulfur Dioxide in Wine Based on a Boron-Doped Diamond Electrode and Reaction Electrochemistry. International journal of molecular sciences, 24(16), 12875. https://doi.org/10.3390/ijms241612875.
9. 11. Halder, B., Ahmadianfar, I., Heddam, S., Mussa, Z. H., Goliatt, L., Tan, M. L., Sa'adi, Z., Al-Khafaji, Z., Al-Ansari, N., Jawad, A. H., & Yaseen, Z. M. (2023). Machine learning-based country-level annual air pollutants exploration using Sentinel-5P and Google Earth Engine. Scientific reports, 13(1), 7968. https://doi.org/10.1038/s41598-023-34774-23
10. 12. Han, L., Zhou, W., Pickett, S. T., Li, W., & Qian, Y. (2018). Multicontaminant air pollution in Chinese cities. Bulletin of the World Health Organization, 96(4), 233–242E. https://doi.org/10.2471/BLT.17.195560
11. 13. Hassaan, M. A., Abdallah, S. M., Shalaby, E. A., & Ibrahim, A. A. (2023). Assessing vulnerability of densely populated areas to air pollution using Sentinel-5P imageries: a case study of the Nile Delta, Egypt. Scientific reports, 13(1), 17406. https://doi.org/10.1038/s41598-023-44186-36.
12. 14. Heue, K. P., Richter, A., Bruns, M., Burrows, J. P., Platt, U., Pundt, I., ... & Wagner, T. (2005). Validation of SCIAMACHY tropospheric NO 2-columns with AMAXDOAS measurements. Atmospheric Chemistry and Physics, 5(4), 1039-1051.
13. 15. Hong, W. Y., Koh, D., & Yu, L. E. (2022). Development and Evaluation of Statistical Models Based on Machine Learning Techniques for Estimating Particulate Matter (PM2.5 and PM10) Concentrations. International journal of environmental research and public health, 19(13), 7728. https://doi.org/10.3390/ijerph19137728
14. 16. Hosseini, V., & Shahbazi, H. (2016). Urban air pollution in Iran. Iranian Studies, 49(6), 1029-1046.
15. 17. Ialongo, I., Bun, R., Hakkarainen, J., Virta, H., & Oda, T. (2023). Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine. Scientific reports, 13(1), 14954. https://doi.org/10.1038/s41598-023-42118-w.
16. 18. Karim, I., & Rappenglück, B. (2023). Impact of Covid-19 lockdown regulations on PM2.5 and trace gases (NO2, SO2, CH4, HCHO, C2H2O2 and O3) over Lahore, Pakistan. Atmospheric environment (Oxford, England : 1994), 303, 119746. https://doi.org/10.1016/j.atmosenv.2023.119746.
17. 19. Mandal, J., Samanta, S., Chanda, A., & Halder, S. (2021). Effects of COVID-19 pandemic on the air quality of three megacities in India. Atmospheric research, 259, 105659. https://doi.org/10.1016/j.atmosres.2021.105659
18. 20. McDuffie, E. E., Sarofim, M. C., Raich, W., Jackson, M., Roman, H., Seltzer, K., Henderson, B. H., Shindell, D. T., Collins, M., Anderton, J., Barr, S., & Fann, N. (2023). The Social Cost of Ozone-Related Mortality Impacts From Methane Emissions. Earth's future, 11(9), 10.1029/2023ef003853. https://doi.org/10.1029/2023ef003853.
19. 21. Nguyen, T. P. M., Bui, T. H., Nguyen, M. K., Nguyen, T. H., Vu, V. T., & Pham, H. L. (2021). Impact of COVID-19 partial lockdown on PM 2.5, SO 2, NO 2, O 3, and trace elements in PM 2.5 in Hanoi, Vietnam. Environmental Science and Pollution Research, 1-11.
20. 22. Niepsch, D., Clarke, L. J., Newton, J., Tzoulas, K., & Cavan, G. (2023). High spatial resolution assessment of air quality in urban centres using lichen carbon, nitrogen and sulfur contents and stable-isotope-ratio signatures. Environmental science and pollution research international, 30(20), 58731–58754. https://doi.org/10.1007/s11356-023-26652-8.
21. 23. Nouri, F., Taheri, M., Ziaddini, M., Najafian, J., Rabiei, K., Pourmoghadas, A., Shariful Islam, S. M., & Sarrafzadegan, N. (2023). Effects of sulfur dioxide and particulate matter pollution on hospital admissions for hypertensive cardiovascular disease: A time series analysis. Frontiers in physiology, 14, 1124967. https://doi.org/10.3389/fphys.2023.1124967.
22. 24. Rabiei-Dastjerdi, H., Mohammadi, S., Saber, M., Amini, S., & McArdle, G. (2022). Spatiotemporal analysis of NO2 production using TROPOMI time-series images and Google Earth Engine in a middle eastern country. Remote Sensing, 14(7), 1725.
23. 25. Rahman M. M. (2023). Recommendations on the measurement techniques of atmospheric pollutants from in situ and satellite observations: a review. Arabian Journal of Geosciences, 16(5), 326. https://doi.org/10.1007/s12517-023-11410-118.
24. 26. Rudke, A. P., Martins, J. A., Hallak, R., Martins, L. D., de Almeida, D. S., Beal, A., Freitas, E. D., Andrade, M. F., Koutrakis, P., & Albuquerque, T. T. A. (2023). Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak. Remote sensing of environment, 289, 113514. https://doi.org/10.1016/j.rse.2023.113514.
25. 27. Singh, V., Singh, S., Biswal, A., Kesarkar, A. P., Mor, S., & Ravindra, K. (2020). Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India. Environmental Pollution, 266, 115368.
26. 28. Tao, M., Fiore, A. M., Jin, X., Schiferl, L. D., Commane, R., Judd, L. M., ... & Tian, Y. (2022). Investigating changes in ozone formation chemistry during summertime pollution events over the Northeastern United States. Environmental Science & Technology, 56(22), 15312.-15327.
27. 29. Taha, R. A., Shalabi, A. S., Assem, M. M., & Soliman, K. A. (2023). DFT study of adsorbing SO2, NO2, and NH3 gases based on pristine and carbon-doped Al24N24 nanocages. Journal of molecular modeling, 29(5), 140. https://doi.org/10.1007/s00894-023-05547-y.
28. 30. Wang, C., Wang, T., & Wang, P. (2019). The spatial–temporal variation of tropospheric NO2 over China during 2005 to 2018. Atmosphere, 10(8), 444.
29. 31. Zhang, Q., Yin, Z., Lu, X., Gong, J., Lei, Y., Cai, B., Cai, C., Chai, Q., Chen, H., Dai, H., Dong, Z., Geng, G., Guan, D., Hu, J., Huang, C., Kang, J., Li, T., Li, W., Lin, Y., Liu, J., … He, K. (2023). Synergetic roadmap of carbon neutrality and clean air for China. Environmental science and ecotechnology, 16, 100280. https://doi.org/10.1016/j.ese.2023.10028.
30. غریبی, شییسته, & کامران. (1400). کاربرد تصاویر ماهواره ای سنتینل 5 در شناسایی کانونهای آلایندههای هوا در ایران. سامانه نشریات علمی, 8(3), 123-138.وا, شایسته, & کامران. (1400). کاربرد تصاویر ماهواره ای سنتینل 5 در شناسایی کانونهای آلایندههای هوا در ایران. سامانه نشریات علمی, 8(3), 123-138.
31. قنادی, محمدامین, شهری, متین, & مرادی, امیررضا. (1401). پایش آلودگی هوا با استفاده از تصاویر ماهواره سنتینل-5 (مطالعه موردی: شهرهای بزرگ صنعتی ایران). فصلنامه علوم محیطی, 20(2), 81-98. doi: 10.52547/envs.2022.1026
32. محمدنژاد آروق، وحید. (1399). شناسایی اراضی شهری با استفاده از تصاویر ماهواره ای سنتینل 1 و 2 بر پایه سامانه گوگل ارث انجین (GEE). پژوهش های جغرافیای برنامه ریزی شهری، 8(3 )، 613-630. SID. https://sid.ir/paper/1063348/fa
33. Adebayo-Ojo, T. C., Wichmann, J., Arowosegbe, O. O., Probst-Hensch, N., Schindler, C., & Künzli, N. (2022). Short-Term Effects of PM10, NO2, SO2 and O3 on Cardio-Respiratory Mortality in Cape Town, South Africa, 2006-2015. International journal of environmental research and public health, 19(13), 8078.
34. Boersma, K. F., Eskes, H. J., & Brinksma, E. J. (2004). Error analysis for tropospheric NO2 retrieval from space. Journal of Geophysical Research: Atmospheres, 109(D4).
35. Cao, Z., Luan, K., Zhou, P., Shen, W., Wang, Z., Zhu, W., Qiu, Z., & Wang, J. (2023). Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean. Toxics, 11(10), 813.
36. Chadwick, G. L., Joiner, A. M. N., Ramesh, S., Mitchell, D. A., & Nayak, D. D. (2023). McrD binds asymmetrically to methyl-coenzyme M reductase improving active-site accessibility during assembly. Proceedings of the National Academy of Sciences of the United States of America, 120(25), e2302815120.
37. Chakrabortty, R., Pal, S. C., Ghosh, M., Arabameri, A., Saha, A., Roy, P., Pradhan, B., Mondal, A., Ngo, P. T. T., Chowdhuri, I., Yunus, A. P., Sahana, M., Malik, S., & Das, B. (2023). Weather indicators and improving air quality in association with COVID-19 pandemic in India. Soft computing, 27(6), 3367–3388.
38. Cooper, M. J., Martin, R. V., Hammer, M. S., Levelt, P. F., Veefkind, P., Lamsal, L. N., ... & McLinden, C. A. (2022). Global fine-scale changes in ambient NO2 during COVID-19 lockdowns. Nature, 601(7893), 380-387.
39. Culková, E., Lukáčová-Chomisteková, Z., Bellová, R., Rievaj, M., Švancarová-Laštincová, J., & Tomčík, P. (2023). An Interference-Free Voltammetric Method for the Detection of Sulfur Dioxide in Wine Based on a Boron-Doped Diamond Electrode and Reaction Electrochemistry. International journal of molecular sciences, 24(16), 12875.
40. Halder, B., Ahmadianfar, I., Heddam, S., Mussa, Z. H., Goliatt, L., Tan, M. L., Sa'adi, Z., Al-Khafaji, Z., Al-Ansari, N., Jawad, A. H., & Yaseen, Z. M. (2023). Machine learning-based country-level annual air pollutants exploration using Sentinel-5P and Google Earth Engine. Scientific reports, 13(1), 7968.
41. Han, L., Zhou, W., Pickett, S. T., Li, W., & Qian, Y. (2018). Multicontaminant air pollution in Chinese cities. Bulletin of the World Health Organization, 96(4), 233–242E.
42. Hassaan, M. A., Abdallah, S. M., Shalaby, E. A., & Ibrahim, A. A. (2023). Assessing vulnerability of densely populated areas to air pollution using Sentinel-5P imageries: a case study of the Nile Delta, Egypt. Scientific reports, 13(1), 17406.
43. Heue, K. P., Richter, A., Bruns, M., Burrows, J. P., Platt, U., Pundt, I., ... & Wagner, T. (2005). Validation of SCIAMACHY tropospheric NO 2-columns with AMAXDOAS measurements. Atmospheric Chemistry and Physics, 5(4), 1039-1051.
44. Hong, W. Y., Koh, D., & Yu, L. E. (2022). Development and Evaluation of Statistical Models Based on Machine Learning Techniques for Estimating Particulate Matter (PM2.5 and PM10) Concentrations. International journal of environmental research and public health, 19(13), 7728.
45. Hosseini, V., & Shahbazi, H. (2016). Urban air pollution in Iran. Iranian Studies, 49(6), 1029-1046.
46. Ialongo, I., Bun, R., Hakkarainen, J., Virta, H., & Oda, T. (2023). Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine. Scientific reports, 13(1), 14954.
47. Karim, I., & Rappenglück, B. (2023). Impact of Covid-19 lockdown regulations on PM2.5 and trace gases (NO2, SO2, CH4, HCHO, C2H2O2 and O3) over Lahore, Pakistan. Atmospheric environment (Oxford, England : 1994), 303, 119746.
48. Mandal, J., Samanta, S., Chanda, A., & Halder, S. (2021). Effects of COVID-19 pandemic on the air quality of three megacities in India. Atmospheric research, 259, 105659.
49. McDuffie, E. E., Sarofim, M. C., Raich, W., Jackson, M., Roman, H., Seltzer, K., Henderson, B. H., Shindell, D. T., Collins, M., Anderton, J., Barr, S., & Fann, N. (2023). The Social Cost of Ozone-Related Mortality Impacts From Methane Emissions. Earth's future, 11(9), 10.1029/2023ef003853.
50. Nguyen, T. P. M., Bui, T. H., Nguyen, M. K., Nguyen, T. H., Vu, V. T., & Pham, H. L. (2021). Impact of COVID-19 partial lockdown on PM 2.5, SO 2, NO 2, O 3, and trace elements in PM 2.5 in Hanoi, Vietnam. Environmental Science and Pollution Research, 1-11.
51. Niepsch, D., Clarke, L. J., Newton, J., Tzoulas, K., & Cavan, G. (2023). High spatial resolution assessment of air quality in urban centres using lichen carbon, nitrogen and sulfur contents and stable-isotope-ratio signatures. Environmental science and pollution research international, 30(20), 58731–58754.
52. Nouri, F., Taheri, M., Ziaddini, M., Najafian, J., Rabiei, K., Pourmoghadas, A., Shariful Islam, S. M., & Sarrafzadegan, N. (2023). Effects of sulfur dioxide and particulate matter pollution on hospital admissions for hypertensive cardiovascular disease: A time series analysis. Frontiers in physiology, 14, 1124967.
53. Rabiei-Dastjerdi, H., Mohammadi, S., Saber, M., Amini, S., & McArdle, G. (2022). Spatiotemporal analysis of NO2 production using TROPOMI time-series images and Google Earth Engine in a middle eastern country. Remote Sensing, 14(7), 1725.
54. Rahman M. M. (2023). Recommendations on the measurement techniques of atmospheric pollutants from in situ and satellite observations: a review. Arabian Journal of Geosciences, 16(5), 326.
55. Rudke, A. P., Martins, J. A., Hallak, R., Martins, L. D., de Almeida, D. S., Beal, A., Freitas, E. D., Andrade, M. F., Koutrakis, P., & Albuquerque, T. T. A. (2023). Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak. Remote sensing of environment, 289, 113514.
56. Singh, V., Singh, S., Biswal, A., Kesarkar, A. P., Mor, S., & Ravindra, K. (2020). Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India. Environmental Pollution, 266, 115368.
57. Tao, M., Fiore, A. M., Jin, X., Schiferl, L. D., Commane, R., Judd, L. M., ... & Tian, Y. (2022). Investigating changes in ozone formation chemistry during summertime pollution events over the Northeastern United States. Environmental Science & Technology, 56(22), 15312.-15327.
58. Taha, R. A., Shalabi, A. S., Assem, M. M., & Soliman, K. A. (2023). DFT study of adsorbing SO2, NO2, and NH3 gases based on pristine and carbon-doped Al24N24 nanocages. Journal of molecular modeling, 29(5), 140.
59. Wang, C., Wang, T., & Wang, P. (2019). The spatial–temporal variation of tropospheric NO2 over China during 2005 to 2018. Atmosphere, 10(8), 444.
60. Zhang, Q., Yin, Z., Lu, X., Gong, J., Lei, Y., Cai, B., Cai, C., Chai, Q., Chen, H., Dai, H., Dong, Z., Geng, G., Guan, D., Hu, J., Huang, C., Kang, J., Li, T., Li, W., Lin, Y., Liu, J., … He, K. (2023). Synergetic roadmap of carbon neutrality and clean air for China. Environmental science and ecotechnology, 16, 100280.
61. Adebayo-Ojo, T. C., Wichmann, J., Arowosegbe, O. O., Probst-Hensch, N., Schindler, C., & Künzli, N. (2022). Short-Term Effects of PM10, NO2, SO2 and O3 on Cardio-Respiratory Mortality in Cape Town, South Africa, 2006-2015. International journal of environmental research and public health, 19(13), 8078. [DOI:10.3390/ijerph19138078.]
62. Boersma, K. F., Eskes, H. J., & Brinksma, E. J. (2004). Error analysis for tropospheric NO2 retrieval from space. Journal of Geophysical Research: Atmospheres, 109(D4).
63. Cao, Z., Luan, K., Zhou, P., Shen, W., Wang, Z., Zhu, W., Qiu, Z., & Wang, J. (2023). Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean. Toxics, 11(10), 813. [DOI:10.3390/toxics11100813.]
64. Chadwick, G. L., Joiner, A. M. N., Ramesh, S., Mitchell, D. A., & Nayak, D. D. (2023). McrD binds asymmetrically to methyl-coenzyme M reductase improving active-site accessibility during assembly. Proceedings of the National Academy of Sciences of the United States of America, 120(25), e2302815120. [DOI:10.1073/pnas.2302815120.]
65. Chakrabortty, R., Pal, S. C., Ghosh, M., Arabameri, A., Saha, A., Roy, P., Pradhan, B., Mondal, A., Ngo, P. T. T., Chowdhuri, I., Yunus, A. P., Sahana, M., Malik, S., & Das, B. (2023). Weather indicators and improving air quality in association with COVID-19 pandemic in India. Soft computing, 27(6), 3367–3388. [DOI:10.1007/s00500-021-06012-9 (Retraction published Soft comput. 2023 May 29;:1-2).]
66. Cooper, M. J., Martin, R. V., Hammer, M. S., Levelt, P. F., Veefkind, P., Lamsal, L. N., ... & McLinden, C. A. (2022). Global fine-scale changes in ambient NO2 during COVID-19 lockdowns. Nature, 601(7893), 380-387.
67. Culková, E., Lukáčová-Chomisteková, Z., Bellová, R., Rievaj, M., Švancarová-Laštincová, J., & Tomčík, P. (2023). An Interference-Free Voltammetric Method for the Detection of Sulfur Dioxide in Wine Based on a Boron-Doped Diamond Electrode and Reaction Electrochemistry. International journal of molecular sciences, 24(16), 12875. [DOI:10.3390/ijms241612875.]
68. Halder, B., Ahmadianfar, I., Heddam, S., Mussa, Z. H., Goliatt, L., Tan, M. L., Sa'adi, Z., Al-Khafaji, Z., Al-Ansari, N., Jawad, A. H., & Yaseen, Z. M. (2023). Machine learning-based country-level annual air pollutants exploration using Sentinel-5P and Google Earth Engine. Scientific reports, 13(1), 7968. [DOI:10.1038/s41598-023-34774-23]
69. Han, L., Zhou, W., Pickett, S. T., Li, W., & Qian, Y. (2018). Multicontaminant air pollution in Chinese cities. Bulletin of the World Health Organization, 96(4), 233–242E. [DOI:10.2471/BLT.17.195560]
70. Hassaan, M. A., Abdallah, S. M., Shalaby, E. A., & Ibrahim, A. A. (2023). Assessing vulnerability of densely populated areas to air pollution using Sentinel-5P imageries: a case study of the Nile Delta, Egypt. Scientific reports, 13(1), 17406. [DOI:10.1038/s41598-023-44186-36.]
71. Heue, K. P., Richter, A., Bruns, M., Burrows, J. P., Platt, U., Pundt, I., ... & Wagner, T. (2005). Validation of SCIAMACHY tropospheric NO 2-columns with AMAXDOAS measurements. Atmospheric Chemistry and Physics, 5(4), 1039-1051.
72. Hong, W. Y., Koh, D., & Yu, L. E. (2022). Development and Evaluation of Statistical Models Based on Machine Learning Techniques for Estimating Particulate Matter (PM2.5 and PM10) Concentrations. International journal of environmental research and public health, 19(13), 7728. [DOI:10.3390/ijerph19137728]
73. Hosseini, V., & Shahbazi, H. (2016). Urban air pollution in Iran. Iranian Studies, 49(6), 1029-1046.
74. Ialongo, I., Bun, R., Hakkarainen, J., Virta, H., & Oda, T. (2023). Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine. Scientific reports, 13(1), 14954. [DOI:10.1038/s41598-023-42118-w.]
75. Karim, I., & Rappenglück, B. (2023). Impact of Covid-19 lockdown regulations on PM2.5 and trace gases (NO2, SO2, CH4, HCHO, C2H2O2 and O3) over Lahore, Pakistan. Atmospheric environment (Oxford, England : 1994), 303, 119746. [DOI:10.1016/j.atmosenv.2023.119746.]
76. Mandal, J., Samanta, S., Chanda, A., & Halder, S. (2021). Effects of COVID-19 pandemic on the air quality of three megacities in India. Atmospheric research, 259, 105659. [DOI:10.1016/j.atmosres.2021.105659]
77. McDuffie, E. E., Sarofim, M. C., Raich, W., Jackson, M., Roman, H., Seltzer, K., Henderson, B. H., Shindell, D. T., Collins, M., Anderton, J., Barr, S., & Fann, N. (2023). The Social Cost of Ozone-Related Mortality Impacts From Methane Emissions. Earth's future, 11(9), 10.1029/2023ef003853. [DOI:10.1029/2023ef003853.]
78. Nguyen, T. P. M., Bui, T. H., Nguyen, M. K., Nguyen, T. H., Vu, V. T., & Pham, H. L. (2021). Impact of COVID-19 partial lockdown on PM 2.5, SO 2, NO 2, O 3, and trace elements in PM 2.5 in Hanoi, Vietnam. Environmental Science and Pollution Research, 1-11.
79. Niepsch, D., Clarke, L. J., Newton, J., Tzoulas, K., & Cavan, G. (2023). High spatial resolution assessment of air quality in urban centres using lichen carbon, nitrogen and sulfur contents and stable-isotope-ratio signatures. Environmental science and pollution research international, 30(20), 58731–58754. [DOI:10.1007/s11356-023-26652-8.]
80. Nouri, F., Taheri, M., Ziaddini, M., Najafian, J., Rabiei, K., Pourmoghadas, A., Shariful Islam, S. M., & Sarrafzadegan, N. (2023). Effects of sulfur dioxide and particulate matter pollution on hospital admissions for hypertensive cardiovascular disease: A time series analysis. Frontiers in physiology, 14, 1124967. [DOI:10.3389/fphys.2023.1124967.]
81. Rabiei-Dastjerdi, H., Mohammadi, S., Saber, M., Amini, S., & McArdle, G. (2022). Spatiotemporal analysis of NO2 production using TROPOMI time-series images and Google Earth Engine in a middle eastern country. Remote Sensing, 14(7), 1725.
82. Rahman M. M. (2023). Recommendations on the measurement techniques of atmospheric pollutants from in situ and satellite observations: a review. Arabian Journal of Geosciences, 16(5), 326. [DOI:10.1007/s12517-023-11410-118.]
83. Rudke, A. P., Martins, J. A., Hallak, R., Martins, L. D., de Almeida, D. S., Beal, A., Freitas, E. D., Andrade, M. F., Koutrakis, P., & Albuquerque, T. T. A. (2023). Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak. Remote sensing of environment, 289, 113514. [DOI:10.1016/j.rse.2023.113514.]
84. Singh, V., Singh, S., Biswal, A., Kesarkar, A. P., Mor, S., & Ravindra, K. (2020). Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India. Environmental Pollution, 266, 115368.
85. Tao, M., Fiore, A. M., Jin, X., Schiferl, L. D., Commane, R., Judd, L. M., ... & Tian, Y. (2022). Investigating changes in ozone formation chemistry during summertime pollution events over the Northeastern United States. Environmental Science & Technology, 56(22), 15312.-15327.
86. Taha, R. A., Shalabi, A. S., Assem, M. M., & Soliman, K. A. (2023). DFT study of adsorbing SO2, NO2, and NH3 gases based on pristine and carbon-doped Al24N24 nanocages. Journal of molecular modeling, 29(5), 140. [DOI:10.1007/s00894-023-05547-y.]
87. Wang, C., Wang, T., & Wang, P. (2019). The spatial–temporal variation of tropospheric NO2 over China during 2005 to 2018. Atmosphere, 10(8), 444.
88. Zhang, Q., Yin, Z., Lu, X., Gong, J., Lei, Y., Cai, B., Cai, C., Chai, Q., Chen, H., Dai, H., Dong, Z., Geng, G., Guan, D., Hu, J., Huang, C., Kang, J., Li, T., Li, W., Lin, Y., Liu, J., … He, K. (2023). Synergetic roadmap of carbon neutrality and clean air for China. Environmental science and ecotechnology, 16, 100280. [DOI:10.1016/j.ese.2023.10028.]
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