بررسی و پایش آلایندهای جوی بر روی ایران با استفاده از ماهواره سنتینل 5

امیدوار, کمال; یوسفی رامندی, روح الله; طوفانی کوپائی, هاجر

doi:10.61186/jsaeh.11.3.3

غریبی, شیوا, شایسته, & کامران. (1400). کاربرد تصاویر ماهواره ای سنتینل 5 در شناسایی کانون‌های آلاینده‌های هوا در ایران. سامانه نشریات علمی, 8(3), 123-138.‎

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.

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

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

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).

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.]

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.

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).

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.

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.]

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).

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.]

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.

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).]

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.

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.

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

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.]

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

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]

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.

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]

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.

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.]

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

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.

16. Hosseini, V., & Shahbazi, H. (2016). Urban air pollution in Iran. Iranian Studies, 49(6), 1029-1046.

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]

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.

Hosseini, V., & Shahbazi, H. (2016). Urban air pollution in Iran. Iranian Studies, 49(6), 1029-1046.

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.

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.]

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

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.]

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.

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]

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.

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.]

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.

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.

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.

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.]

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.

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.]

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.

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.

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.

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.]

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.‌

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.]

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.

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.‌

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.

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.

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.

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.

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.]

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.‎

Wang, C., Wang, T., & Wang, P. (2019). The spatial–temporal variation of tropospheric NO2 over China during 2005 to 2018. Atmosphere, 10(8), 444.

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.‎

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

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.]

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

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

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Hosseini, V., & Shahbazi, H. (2016). Urban air pollution in Iran. Iranian Studies, 49(6), 1029-1046.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.‌

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.

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.

Wang, C., Wang, T., & Wang, P. (2019). The spatial–temporal variation of tropospheric NO2 over China during 2005 to 2018. Atmosphere, 10(8), 444.

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.