تحلیل فضایی مخاطرات محیطی

تحلیل فضایی مخاطرات محیطی

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

نویسندگان
کمال امیدوار
روح الله یوسفی رامندی
هاجر طوفانی کوپائی
دانشگاه یزد
10.61186/jsaeh.11.3.3
چکیده
آلودگی هوا می تواند اثرات منفی جدی بر سلامت انسان از جمله بیماری های قلبی عروقی و تنفسی داشته باشد. پایش و کنترل آلاینده های هوا برای حفاظت از سلامت عمومی و محیط زیست بسیار مهم است. کشور ایران مانند بسیاری از کشورهای در حال توسعه با آلودگی هوا به ویژه در کلان شهرها و شهرهای صنعتی خود مواجه است. یکی از ابزارهای قدرتمند در پایش آلودگی هوا، روش های مبتنی بر سنجش از دور می باشد.هدف این مطالعه استفاده از داده‌های ماهواره‌ای با وضوح نسبتاً بالا برای پایش کیفیت هواو میزان آلودگی هوا با استفاده از تصاویر سنجنده سنتینل-5(Sentinel-5P)است.در این مطالعه، پایشی جامع براساس مقادیر برخی از مهمترین آلاینده ­های هوا (از جمله AI،O3،NO2،SO2,CH4وCO)، با استفاده از تصویرهای ماهواره سنتینل-5 برای کشور ایران در سالهای 2019 -2023 صورت گرفته است. نتایج این تحقیق نشان داد ، که انتشار گاز های مونو اکسید کربن و دی اکسید گوگرد روند کاهشی(در ماه های ژوئن بعنوان نمونه ماه مورد بررسی) داشته ، اما گاز دی اکسید نیتروژن،گاز متان، گاز ازن و آئروسلها روند افزایشی را طی ماه های ژوئن 2021 تا 2023 داشته اند. به طور کلی، آلودگی هوا در بخش‌های شمالی کشور، به‌ویژه در شهرهای بزرگ و چند تجمع بزرگ شهری بسیار جدی‌تر است، در مطالعه حاضر ، بررسی شد که چگونه سطح شش آلاینده هوا در کشور ایران در ماه های ژوئن 2019 تا 2023 متغیر و متفاوت هستند. از دیگر نتایج مهم این تحقیق این است که در مجموع میزان آلودگی هوا در سالهای 2020-2023 در مقایسه با سال 2019 با روندی افزایشی مواجه شده است. همچنین پایش صورت گرفته بوسیله تصویرهای ماهواره سنتینل-۵ نشان می ­دهد که در سال های اخیر، تهران آلوده ­ترین هوا را به لحاظ مجموع گازهای مونوکسید کربن، دی اکسید نیتروژن، دی اکسید گوگرد و ذرات معلق (گرد و غبار) داشته است. همچنین تغییرات غلظت آلاینده ها از الگوی خاصی تبعیت نمی‌کند. همچنین مشخص شد سامانه GEE قادر است حجم زیادی از داده ها را در زمان بسیار اندک با دقت بالا پردازش کند.
کلیدواژه‌ها
آلاینده ها
آلودگی
متان (CH4)
مونوکسید کربن (CO)
دی اکسید نیتروژن(NO2)
ازن (O3)
دی اکسید گوگرد(SO2)و آئروسل(AI)
Sentinel-5P

عنوان مقاله English

Investigation and monitoring of atmospheric pollution over Iran using Sentinel 5 satellite

نویسندگان English

Kamal omidvar
rohollah yousefi ramandi
hajar toofani
Yazd University
چکیده English

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.

کلیدواژه‌ها English

Pollutants
Pollution
methane (CH4)
carbon monoxide (CO)
nitrogen dioxide (NO2)
Ozone (O3)
sulfur dioxide (SO2) and aerosol (AI)
Sentinel-5P
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.
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.]
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.
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.
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.
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.
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.
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.
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.
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.
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.